Grain assemblages and diagenesis in organic-rich mudrocks, Upper Pennsylvanian Cline shale (Wolfcamp D), Midland Basin, Texas

ABSTRACT

Grain assemblages in the organic-rich Cline shale in the Midland Basin are dominated by components of extrabasinal derivation (11.4 to 98.5 vol. %; average volume: 82.6%). Major extrabasinal components include K-rich clay minerals, detrital quartz, albite, K-feldspar, micas, and lithic fragments. Intrabasinal components include mainly biosiliceous allochems (sponge spicules and radiolarians), agglutinated foraminifera, Ca-phosphate peloids, clay-rich peloids, organomineralic aggregates, intraclasts, and other biocalcareous allochems. Authigenic minerals are most evident as grain replacements, euhedral ankerite, Ca-phosphate cement, and precipitates in large pores. A strongly localized spatial distribution of diagenetic products at micron to centimeter scales is observed in most siliciclastic samples, except in biosiliceous allochem-rich ones in which abundant intergranular pore-filling clay-size microquartz cement is observed. Compaction is evident in the Cline shale because of low porosity and generally low cement volumes. Neither textural variation nor bulk mineral composition alone is sufficient to confidently decipher the rock bulk property (e.g., total organic carbon) and reservoir quality variation (e.g., porosity and permeability). However, a good negative relationship between the ratio of extrabasinal to intrabasinal grains and favorable reservoir properties is observed in the Cline shale. Specifically, higher porosity, permeability, and total organic carbon are observed in samples representing the extreme end members of intrabasinal-derived biosilica-rich layers. Nickel, a recognized proxy for paleoproductivity, exhibits a positive relationship with intrabasinal grain content and reservoir properties. X-ray fluorescence–based analysis of nickel can be a rapid and cost-effective way to delineate favorable unconventional reservoir quality in the Cline shale.

INTRODUCTION

Despite the status of fine-grained sedimentary rocks (shales, mudstones, and mudrocks) as being the most abundant sedimentary rock type (Folk, 1980) and having global economic significance (Jarvie et al., 2007; Jarvie, 2012; Zou et al., 2013; Hackley and Cardott, 2016), uncertainties remain concerning the manner in which their basic components affect bulk properties (e.g., total organic carbon [TOC]) and reservoir quality (e.g., porosity and permeability).

Heterogeneity of mineral composition, grain assemblages, textural variation, and reservoir quality in organic-rich mudrocks have been well documented in previous studies (e.g., MacQuaker and Gawthorpe, 1993; Macquaker and Howell, 1999; Macquaker and Adams, 2003; Loucks and Ruppel, 2007; Macquaker et al., 2010; Aplin and Macquaker, 2011; Bohacs et al., 2014; K. Milliken, 2014; Lazar et al., 2015; Fairbanks et al., 2016). However, previous work focused mainly on the qualitative description of heterogeneities at multiple scales (from thin section to outcrop). The particular impact of the type of grain assemblage on diagenetic pathways and reservoir quality evolution in mudrocks remains somewhat uncertain and, as a result, is little applied in unconventional reservoir exploration and development. One reason for this uncertainty is the extremely small size of the component grains in mudrocks, which makes direct observation difficult (Folk, 1980). K. Milliken (2014) suggested that most particles in mudrocks are smaller than 30 μm, which is a standard thickness for thin sections. In such fine-grained sedimentary rocks, the identification of grain assemblages and diagenetic features is difficult when using conventional optical microscopy and inadequately captured by scanning electron microscopy (K. Milliken, 2014). Another reason for uncertainty is that the compositional variation in grain assemblages in mudrocks is complex and can include both intrabasinal and extrabasinal particles (e.g., K. Milliken, 2014). Specifically, intrabasinal components include biocalcareous allochems (Denne et al., 2014), biosiliceous allochems (Ellis, 1963; Isaacs, 1981; Young and Moore, 1994; Fishman et al., 2015), organic allochems (water-column dwellers; Passey et al., 2010), and organomineralic aggregates (OMAs) (Macquaker et al., 2010), whereas extrabasinal components mainly include detrital quartz, feldspar, lithic fragments, heavy minerals, terrigenous organic matter (OM), and detrital clay minerals. Such grain-assemblage variations plausibly cause diverse pathways of diagenesis and thus result in different reservoir properties (e.g., porosity, permeability, and mechanical moduli; K. Milliken, 2014).

The Upper Pennsylvanian Cline shale in the Midland Basin, Texas, has long been recognized as an important source rock for productive reservoirs in the basin (Klemme and Ulmishek, 1991). Heightened industry focus on the Cline shale is a result of newly discovered producible unconventional petroleum resources in this marine shale system (Hamlin and Baumgardner, 2012). However, little documentation of primary grain assemblages, diagenetic features, and rock properties of the Cline shale has been published. Previous studies (K. Milliken, 2014; K. L. Milliken et al., 2017, 2018) indicated that primary grain assemblages (i.e., intrabasinal and extrabasinal grains) with different mechanical and chemical properties are a key factor controlling diagenetic pathway and thus determined bulk reservoir properties, such as porosity, permeability, TOC, and mechanical moduli, in several hydrocarbon-producing shale reservoirs (e.g., Barnett, Eagle Ford, and Yanchang). Theoretically, this conclusion from other hydrocarbon-producing shale systems can be also applied to the Cline shale, which has a similar depositional background. Here, we report a case study of how the primary grain assemblages affect diagenetic pathways and rock property (porosity, permeability, and TOC) evolution in the Cline shale of the Midland Basin with the goal of elucidating general principles that can inform models for hydrocarbon exploration in fine-grained sedimentary systems.

GEOLOGICAL BACKGROUND

The Cline shale (Wolfcamp D) was deposited in the Midland Basin, an epicratonic foreland basin of the Ouachita orogenic belt and the eastern secondary subsidence tectonic unit of the greater Permian Basin (Figure 1; Yang and Dorobek, 1995). During the Late Pennsylvanian, a time of accelerated subsidence of the Midland Basin, deposition of the Cline shale occurred in the basin, and the Cisco and Canyon Groups of mixed siliciclastic–carbonate composition took place on the Eastern shelf and adjacent area (Wright, 2011; Baumgardner et al., 2016). Since 2009, the Cline shale has been drilled as an unconventional oil reservoir and has been considered as a secondary target in developing the Midland Basin unconventional resource plays (Roush, 2015). For operational purposes, the petroleum industry has long referred to the Cline shale as the Wolfcamp D interval.

Figure 1. Map of the Midland Basin showing the distribution of the Cline shale, general structural features, location of cores, and regional cross section. Map modified from Wright (2011) and Baumgardner et al. (2016). Bold, dotted black lines are the boundary of tectonic unit. CBP = Central Basin platform; DB = Delaware Basin; ES = Eastern shelf; HA = Horseshoe atoll; MA = Matador arch; MB = Midland Basin; NM = New Mexico; NWS = Northwest shelf; OA = Ozona arch; SC = Sheffield channel; TEX = Texas.

The Cline shale of the Midland Basin is underlain by Strawn carbonates and overlain by Wolfcamp strata (Figure 2) and has a thickness ranging from 200 to 425 ft (60 to 130 m) (Roush, 2015). Published structure maps indicate that the Cline shale dips westward (Baumgardner et al., 2016). The Cline shale is bounded by the Eastern shelf to the east, the Central Basin platform to the west, the Ozona arch to the southwest, and the Horseshoe atoll to the north (Figure 1). These four distinct boundaries make the Cline shale a relatively restricted depositional unit.

Figure 2. General stratigraphy of the Upper Pennsylvanian to lower Permian section in the Midland Basin. Location of the section was shown in Figure 1. Top of Strawn Formation carbonate is used as datum. Horizontal red lines represent formation boundary. Jagged black lines represent well logs. GR = gamma ray in API units; RES = resistivity in ohm-meters; SON = sonic in microseconds per feet.

During sea-level highstand, sediment input to the basin comprised dominantly a combination of platform-derived wackestone, pelagic calcareous mudrocks, and fine-grained siliciclastics, primarily comprising windblown clay (Brown et al., 1990). By contrast, during sea-level lowstand, platforms were exposed, and siliciclastic sediment-transport systems extended across the wide platform and input directly into the basin (Brown et al., 1990). The Wichita Mountains and the Arbuckle–Criner Hill uplift to the north of the basin provided terrigenous clastics to the basin and the Ouachita orogenic belt to the east of the Eastern shelf is another important clastic source area (Brown et al., 1990).

Global plate reconstructions by Blakey (2003) suggested that during the Late Pennsylvanian, the Midland Basin occupied a narrow inland seaway (Great Permian seaway) bounded by the Laurussian continent to the north and Gondwana to the south. Water circulation in the Midland Basin was restricted by stratification (development of both a thermocline and chemocline), forming the bottom anoxic environment (Algeo and Heckel, 2008). Water depths across the southern Midland Basin are difficult to estimate. Algeo and Heckel (2008) suggested that bathymetric variation in the Permian Basin region during the Late Pennsylvanian was considerable, with deep basins (hundreds of meters) separated by shallower sills that formed over structural highs. This range of water depth is similar to the early Permian Wolfcamp basinal setting in the Midland Basin, which is estimated to be 1000–2000 ft (300–600 m; Baumgardner et al., 2016).

SAMPLING AND ANALYTICAL METHODS

The four cores from the southern Midland Basin used in this study are located in Sterling, Reagan, Glasscock, and Martin Counties (Figure 1). The core from the Horwood 2151-H well is continuous (273 ft [83 m] in total) and penetrates through the whole Cline shale (Figure 2). The Greer O. L. 2, Glass G. W. 3-B, and Powell E. L. 1 wells are cored only in several short intervals (Figure 2). All of these cores are stored at the Core Research Center, Bureau of Economic Geology, The University of Texas at Austin.

Figure 3. Simplified core description of Horwood 2151-H with sample locations. Mudrock terminology used here is modified from Lazar et al. (2015). Left-point arrows indicate the direction of increasing grain size. ID = identification number.

In total, 140 samples were taken from four wells to prepare polished thin sections. Among these 140 samples, 35 were chosen for systematic bulk mineralogy x-ray diffraction (XRD) analysis, TOC analysis, field-emission scanning electron microscopy observation, whole-rock elemental analysis by x-ray fluorescence (XRF), and porosity and permeability measurement (using the Gas Research Institute [GRI] method; Guidry et al., 1996). For these 35 chosen samples, the Horwood 2151-H well was sampled in detail (32 samples) to assess mudrock heterogeneity in grain assemblages, petrophysical properties, and geochemical properties (Figure 3); the other 3 samples are from the remaining three wells (Table 1). The following were used as sampling criteria: (1) volumetrically significant major and minor lithologies and (2) material that is as homogeneous as possible within the individual sampling intervals (<2 in.) so that the different types of analyses made on subsamples can be correlated.

Bulk Composition Analysis

Element analyses were undertaken using Bruker Elemental Tracer IV-SD energy-dispersive XRF equipment. The XRF spectra for major elements were generated under vacuum using a rhodium (Rh) tube set at 15 kilovolts (kV) and 34.4 microampules (μA) for a count time of 60 s. The XRF spectra for trace elements were analyzed at 40 kV and 25 μA, with an Al-Ti-copper (Cu) filter on the equipment and a count time of 60 s. Core samples were analyzed by placing the flat slab side down on the nose of the instrument. Calibration during and after measurement rigorously followed the workflow proposed by Rowe et al. (2012).

The XRD, TOC, and GRI’s crushed-rock porosity and permeability measurement were completed by FireWheel Energy LLC (Houston, Texas). X-ray patterns of the sample powders (∼500 mg) are recorded on a Bruker D8 Advance powder x-ray Diffractometer using Cu radiation (40 kV and 100 milliampules) from a long line focus tube, a graphite monochromator in the diffracted beam, and a vacuum device to minimize absorption of the x-rays by air. Identification of minerals is made using EVA software (Bruker AXS Inc.) by comparison to reference mineral patterns archived in the Powder Diffraction Files of the International Centre for Diffraction Data. The XRD results are given as weight percentage. These analytical data were previously reported in the appendix of Zheng (2016).

Imaging Technology

Uncovered polished thin sections of approximately 25 μm thickness were produced for optical microscopy and scanning electron microscope (SEM) imaging. Samples were first inspected using conventional petrographic microscopy and were then coated with approximately 25 nanometers carbon (C) before being examined in the Field Electron and Ion Nova NanoSEM 430 field emission-SEM. All 35 samples were examined using both secondary electron (SE) and backscattered electron (BSE) modes. Elemental and mineral composition was identified by x-ray energy-dispersive spectroscopy (EDS) mapping. A unified scheme of false color was applied to the major mudrock elements to discriminate minerals: potassium (K) (yellow; K-feldspar, muscovite, and K-clay); silicon (red; quartz); sodium (Na) (aqua; Na-feldspar); magnesium (Mg) (fuchsia; dolomite, chlorite); calcium (Ca) (blue; calcite); iron (yellow; pyrite); and C (orange; OM). Twin 30-mm2 Bruker XFlash silicon drift detector EDS detectors were equipped using 15 kV accelerating voltage, 5.0 μm spot size, 30 μm aperture, a working distance of approximately 9–10 mm, and more than 500 s scanning time. Cathodoluminescence (CL) imaging using a Gatan ChromaCL detector was conducted on some specific samples to distinguish authigenic quartz and detrital quartz. The CL imaging was performed using 15 kV accelerating voltage, 5.0 μm spot size, 40 μm aperture, a working distance of approximately 12–13 mm, and 10 min of scanning time. The EDS maps were mixed with BSE maps, and the CL maps were mixed with the SE signal to create the images presented in this study.

Point-Count and Grain-Tracing Methods

A grain-assemblage point count was conducted on EDS maps using the image analysis program JMicrovision© (Roduit, 2008). The EDS mapping was performed at magnifications of 2500× to 3000× for all samples in this study. This is because we can confidently identify detrital silt particles at these magnifications. Areas having anomalously large allochems (commonly extra large, robust molluscan skeletal and agglutinated foraminifera) were intentionally avoided. Two images were taken of each sample to obtain a 200 × 200 μm2 area, which we believe approaches the representative elementary area suggested for mudrocks in previous studies (Yoon and Dewers, 2013; Houben et al., 2014; Kelly et al., 2016). For each image, 200 random points were counted (a total of 400 points for each sample).

Particle-size determination for the silt fraction (grain size between 4 and 9 ϕ or 63 and 2 μm) was performed on BSE images within the area of point counting. A boundary of 2 μm is used in this study to distinguish silt-size particles and clay-size particles. This is because we can confidently identify detrital particles of 2-μm diameter under SEM magnifications of 2500× to 3000×. Grain outlines were manually traced using the image analysis program JMicrovision (Roduit, 2008). Grain size is expressed as equivalent circular diameter (ECD), which by definition is the diameter of a circle having the same area as that of the object. All grains greater than 2 μm (>0.00008 in.) or 9 ϕ, except authigenic crystals, which were fully within the field of view, were included in the measurement. Mean grain size data from these all-grain images were corrected to standard volume-weighted mean grain size based on the grain area fraction (individual grain areas are normalized to total grain area, a proxy for volume).

RESULTS

Bulk Composition and Lithology

Bulk composition analysis data in this study, including XRF, XRD, TOC, porosity, and permeability, are given in Table 1 and the Appendix (supplementary material available as AAPG Datashare 120 at www.aapg.org/datashare). Clay minerals are the most important component in the Cline shale, ranging from 4 to 61 wt. % (mean of 40 wt. %; Table 1). Excluding kaolinite (authigenic pore filling) and chlorite (also dominantly authigenic), the average content of probable detrital clay (reported as smectite, illite, and mixed-layer illite–smectite in Table 1) is approximately 36 wt. %, ranging from 4 to 53 wt. %. Pore-filling crystalline illite can also be identified locally. Quartz is another important mineral in the Cline shale, ranging from 3 to 66 wt. % (mean of 34 wt. %). Carbonate minerals, including calcite, dolomite, ankerite, and siderite, are abundant in only three samples (i.e., samples 15, 39, and 54) of the wackestone and calcareous mudrock facies (Table 1). Excluding these three carbonate samples, calcite is detected in all but four of the samples, averaging approximately 3 wt. % and ranging from below detection to 20 wt. %, whereas dolomite and ankerite range from below detection to 8 wt. % (mean of 2 wt. %) and below detection to 4 wt. % (mean of 1 wt. %), respectively. Feldspars, including plagioclase and K-feldspar, are also important components, averaging 9 wt. % and ranging from below detection to 17 wt. %. Pyrite ranges from below detection to 10 wt. % (mean of 4 wt. %). Other minor minerals detected by XRD include siderite, barite, and apatite (Table 1).

Figure 4. Textural variations observed in backscattered electron images. Images for samples 20, 48, 61, and 84 illustrate variations in silt and sand content. Data obtained from JMicrovision (Roduit, 2008). The four samples selected represent important textural variations: sample 84 contains the finest mean silt size (8.35 ϕ); sample 61 contains the least silt (10.2%) but has a coarser mean grain size than sample 84; sample 48 contains abundant silt and also sand-size particles; sample 20 contains the highest silt content (31.6%). Examples of silt- and sand-size particles are labeled “s” in each image. Detrital dolomite (labeled “d”) with ankerite rim (red arrow), ankerite (labeled “a”), pyrite (labeled “py”), and silt-size micas (labeled “m”) are also observed in some samples. The red dashed line boxes highlight regions rich in clay-size matrix.

The lithofacies nomenclature of mudrocks used in this study is modified from the compositional classification proposed by Lazar et al. (2015). Mudrocks dominated by quartz; carbonate (e.g., calcite, dolomite, etc.); or clay minerals (e.g., illite, smectite, etc.) are named “siliceous mudrock,” “calcareous mudrock,” and “argillaceous mudrock,” respectively. Based on the XRD analysis of 15 mineral compositions (Table 1) and petrographic observations (described below), 4 lithologies were recognized: siliceous mudrocks, calcareous mudrocks, argillaceous mudrocks, and wackestone (Figure 3; Table 1). The TOC varies significantly, even for the same lithofacies over short vertical distances. Measured TOC ranges from 0.13 to 8.32 wt. % with a mean value of 3.48 wt. % (Table 1).

Textural Variation

All of the samples examined in this study are composed of clay- and silt-size grains, except sample 48, which also contains a substantial amount of sand-size particles (19.6 vol. %). Silt plus sand content ranges from 10.2 to 44.6 vol. % (Table 2). The corrected mean ECD of silt and sand grains ranges from 4.04 to 8.35 ϕ. The ϕ standard deviation ranges from 0.39 to 1.07, which suggests a wide range of grain sorting. Some examples of end-member textures of the silt- and sand-size particle distribution pattern are shown in Figures 4 and 5. Based on the textural classification of Macquaker and Adams (2003), all of the samples belong to silt-bearing clay-rich mudstone, except sample 48, which is sand- and silt-bearing clay-rich mudstone (Table 2).

Figure 5. Variations in the particle-size distribution of the four samples in Figure 4.

Major Extrabasinal Grains

In general, extrabasinal particles include detrital quartz, feldspar, lithic fragments, mica, and terrigenous OM (Figures 6). Detrital silt-size quartz is very common in most of the Cline shale. Detrital quartz is characterized by its angular shape (Figures 6). Figures 7 shows the most common reddish CL color of silt-size detrital quartz. Some specific silt-size detrital quartz can exhibit CL color from dark red to bright blue (Figure 7C, D). Some fabrics, such as microfractures and overgrowth zones of detrital quartz, can also be identified by CL (Figure 7C, D).

Figure 6. Major extrabasinal components observed in x-ray energy-dispersive spectroscopy mapping, sample 34. Silt-size detrital quartz, K-mica, Mg-mica, albite, and K-feldspar are abundant in rocks. The dominant clay mineral is K rich. Bulk x-ray diffraction analysis data indicate that this clay may most likely be a mixed layer of illite–smectite and illite. BSE = backscattered electron.

Detrital silt-size feldspar includes K-feldspar and albite (Figures 6). The most common lithic grains are quartz-feldspar aggregates, which may correspond to plutonic rock fragments (Folk, 1980; K. L. Milliken et al., 2017) (Figures 6). Monocrystalline micas include K-rich mica (muscovite) and Mg-rich mica (chlorite) (Figures 6).

Figure 7. Representative extrabasinal detrital quartz in the Cline shale. (A) X-ray energy-dispersive spectroscopy map of agglutinated foraminifera (dark-blue dashed line); sample 37. (B) Cathodoluminescence image of a close-up area in (A). Detrital quartz exhibits a reddish color. White arrows indicate quartz cement. (C) Cathodoluminescence image of detrital quartz shows cathodoluminescence color range from dark red to bright blue. White arrows indicate quartz cement; sample 48. (D) Cathodoluminescence image of detrital quartz shows cathodoluminescence color range from dark red to bright blue. The white arrow indicates quartz cement (dark-blue color); sample 83. BSE = backscattered electron.

A component of terrigenous OM (woody material characterized by particle shapes that reflect the cell structure typical of woody material) is present in the silt- and sand-size fraction (Figure 8A), but the volume of this material is relatively minor compared to other OM types (refer to next section).

Figure 8. Organic matter types identified in the Cline shale. (A) Organic matter particle of likely terrigenous origin (white arrow), sample 63. (B) Possible algal spore (white arrow); sample 43. (C) Possible algal spore (white arrow) partially collapsed by compaction, sample 12. (D) Migrated bitumen (white arrow), sample 47. det = detector; det BSED = backscattered electron detector; HFW = horizontal field width; HV = accelerating voltage; mag = magnification; spot = spot size; WD = working distance.

The dominant clay mineral is K rich (Figures 6). Bulk XRD analysis data indicate that this clay may most likely be a mixed layer of illite–smectite and illite.

Three carbonate samples (i.e., samples 5, 15, and 39) have experienced heavy diagenesis overprinting; thus, the original grain assemblage cannot be identified with precision. As a result, little information of grain assemblage can be obtained from them. Except for carbonate samples, extrabasinal grains account for approximately 87.5 vol. % of total grains, ranging from 69.5 to 98.5 vol. % on the basis of point count (Appendix, supplementary material available as AAPG Datashare 120 at www.aapg.org/datashare).

Figure 9. Representative intrabasinal grains in the Cline shale. (A) X-ray energy-dispersive spectroscopy map showing sponge spicule, sample 59; (B) x-ray energy-dispersive spectroscopy map showing radiolaria (replaced by ankerite) and pore-filling kaolinite, sample 39; (C) agglutinated foraminifera (AF) (dashed blue line), backscattered electron (BSE) image, sample 2; (D) x-ray energy-dispersive spectroscopy map showing molluscan skeletal fragment, sample 34; (E) AF (partly replaced by pyrite) and organomineralic aggregates (OMAs) (dashed blue line), BSE image, sample 1; and (F) x-ray energy-dispersive spectroscopy map showing plausible Ca-phosphate peloids (arrows), sample 35. det = detector; det BSED = backcattered electron detector; HFW = horizontal field width; HV = accelerating voltage; mag = magnification; spot = spot size; WD = working distance.

Major Intrabasinal Grains

Criteria for identification of intrabasinal grains follow Scholle and Ulmer-Scholle (2003). Intrabasinal grains are identified based on their size, shape, internal structure, mineral composition, and age range. Major intrabasinal particles observed under the SEM include biosiliceous allochems (sponge spicules and radiolarians; Figure 9A, B); agglutinated foraminifera (Figure 9C), biocalcareous allochems (Figure 9D); OMAs (Figure 9E); Ca-phosphate peloids (Figure 9F); and intraclasts (phosphatic grains, vertebrate bones and teeth, and glauconite; Figure 10).

Figure 10. Representative intraclasts in the Cline shale. (A) Phosphatic grains (black arrows) occur with detrital silt quartz, suggesting reworked deposition, transmitted light, sample 61; (B) phosphatic-coated grain (yellow arrows), massive skeletal fragment of a shallow-platform dweller suggests downslope transportation, transmitted light, Horwood 2151-H, 7991.1 ft; (C) locally abundant glauconite (green), transmitted light, Glass G. W. 3-B, 10,402.9 ft; and (D) vertebrate bone, transmitted light, Horwood 2151-H, 7982.7 ft.

Emphasis Article

New Ways of Evaluating Sweet Spots Take Hold

Unconventional plays in the Permian Basin are nothing new t...

Emphasis Article

Decoding the Permian

Fasken Oil and Drilling Info have a data set encompassing hundreds of square miles and tho...

Article

Unorthodox Plays Can Muddy Roles

The role of geology is fairly well-defined in conventional...

Article

AAPG and the Apollo 11 Golden Anniversary

On July 16, 1969, at 9:32 a.m. Eastern Daylight time, Apoll...

Bulletin Article

Constraining the origin of reservoirs formed...

The presence of hydrocarbon-bearing sandstones within the E...

Emphasis Article

Combined Approach Used to Tackle Fracture Mo...

After many months of harnessing mind-bending ideas, a Houst...

Article

Training Center Opens in London

AAPG takes its first steps in bringing training centers to...

Bulletin Article

Prediction of channel connectivity and fluvi...

Predicting the presence and connectivity of reservoir-quali...

Article

First 'WinGS' Scholarship Awarded by West Te...

As women continue to make inroads and contributions to the ...

Bulletin Article

Measuring and modeling fault density for CO2...

Emission of carbon dioxide (CO2) from fossil-fueled power g...

Bulletin Article

Salt structures and hydrocarbon accumulation...

The Tarim Basin is one of the most important hydrocabon-bea...

Bulletin Article

Geothermal convection in South Atlantic subs...

Prolific hydrocarbon discoveries in the subsalt, commonly k...

Emphasis Article

Wireless Seismic Expanding in Marketplace

Here, there and everywhere: For the first time, cable-free...

Article

Annual G-Camp Goes Virtual

After 13 years of taking teachers into the field, this year's G-Camp was held virtually in...

Please log in to read the full article

ABSTRACT

Grain assemblages in the organic-rich Cline shale in the Midland Basin are dominated by components of extrabasinal derivation (11.4 to 98.5 vol. %; average volume: 82.6%). Major extrabasinal components include K-rich clay minerals, detrital quartz, albite, K-feldspar, micas, and lithic fragments. Intrabasinal components include mainly biosiliceous allochems (sponge spicules and radiolarians), agglutinated foraminifera, Ca-phosphate peloids, clay-rich peloids, organomineralic aggregates, intraclasts, and other biocalcareous allochems. Authigenic minerals are most evident as grain replacements, euhedral ankerite, Ca-phosphate cement, and precipitates in large pores. A strongly localized spatial distribution of diagenetic products at micron to centimeter scales is observed in most siliciclastic samples, except in biosiliceous allochem-rich ones in which abundant intergranular pore-filling clay-size microquartz cement is observed. Compaction is evident in the Cline shale because of low porosity and generally low cement volumes. Neither textural variation nor bulk mineral composition alone is sufficient to confidently decipher the rock bulk property (e.g., total organic carbon) and reservoir quality variation (e.g., porosity and permeability). However, a good negative relationship between the ratio of extrabasinal to intrabasinal grains and favorable reservoir properties is observed in the Cline shale. Specifically, higher porosity, permeability, and total organic carbon are observed in samples representing the extreme end members of intrabasinal-derived biosilica-rich layers. Nickel, a recognized proxy for paleoproductivity, exhibits a positive relationship with intrabasinal grain content and reservoir properties. X-ray fluorescence–based analysis of nickel can be a rapid and cost-effective way to delineate favorable unconventional reservoir quality in the Cline shale.

INTRODUCTION

Despite the status of fine-grained sedimentary rocks (shales, mudstones, and mudrocks) as being the most abundant sedimentary rock type (Folk, 1980) and having global economic significance (Jarvie et al., 2007; Jarvie, 2012; Zou et al., 2013; Hackley and Cardott, 2016), uncertainties remain concerning the manner in which their basic components affect bulk properties (e.g., total organic carbon [TOC]) and reservoir quality (e.g., porosity and permeability).

Heterogeneity of mineral composition, grain assemblages, textural variation, and reservoir quality in organic-rich mudrocks have been well documented in previous studies (e.g., MacQuaker and Gawthorpe, 1993; Macquaker and Howell, 1999; Macquaker and Adams, 2003; Loucks and Ruppel, 2007; Macquaker et al., 2010; Aplin and Macquaker, 2011; Bohacs et al., 2014; K. Milliken, 2014; Lazar et al., 2015; Fairbanks et al., 2016). However, previous work focused mainly on the qualitative description of heterogeneities at multiple scales (from thin section to outcrop). The particular impact of the type of grain assemblage on diagenetic pathways and reservoir quality evolution in mudrocks remains somewhat uncertain and, as a result, is little applied in unconventional reservoir exploration and development. One reason for this uncertainty is the extremely small size of the component grains in mudrocks, which makes direct observation difficult (Folk, 1980). K. Milliken (2014) suggested that most particles in mudrocks are smaller than 30 μm, which is a standard thickness for thin sections. In such fine-grained sedimentary rocks, the identification of grain assemblages and diagenetic features is difficult when using conventional optical microscopy and inadequately captured by scanning electron microscopy (K. Milliken, 2014). Another reason for uncertainty is that the compositional variation in grain assemblages in mudrocks is complex and can include both intrabasinal and extrabasinal particles (e.g., K. Milliken, 2014). Specifically, intrabasinal components include biocalcareous allochems (Denne et al., 2014), biosiliceous allochems (Ellis, 1963; Isaacs, 1981; Young and Moore, 1994; Fishman et al., 2015), organic allochems (water-column dwellers; Passey et al., 2010), and organomineralic aggregates (OMAs) (Macquaker et al., 2010), whereas extrabasinal components mainly include detrital quartz, feldspar, lithic fragments, heavy minerals, terrigenous organic matter (OM), and detrital clay minerals. Such grain-assemblage variations plausibly cause diverse pathways of diagenesis and thus result in different reservoir properties (e.g., porosity, permeability, and mechanical moduli; K. Milliken, 2014).

The Upper Pennsylvanian Cline shale in the Midland Basin, Texas, has long been recognized as an important source rock for productive reservoirs in the basin (Klemme and Ulmishek, 1991). Heightened industry focus on the Cline shale is a result of newly discovered producible unconventional petroleum resources in this marine shale system (Hamlin and Baumgardner, 2012). However, little documentation of primary grain assemblages, diagenetic features, and rock properties of the Cline shale has been published. Previous studies (K. Milliken, 2014; K. L. Milliken et al., 2017, 2018) indicated that primary grain assemblages (i.e., intrabasinal and extrabasinal grains) with different mechanical and chemical properties are a key factor controlling diagenetic pathway and thus determined bulk reservoir properties, such as porosity, permeability, TOC, and mechanical moduli, in several hydrocarbon-producing shale reservoirs (e.g., Barnett, Eagle Ford, and Yanchang). Theoretically, this conclusion from other hydrocarbon-producing shale systems can be also applied to the Cline shale, which has a similar depositional background. Here, we report a case study of how the primary grain assemblages affect diagenetic pathways and rock property (porosity, permeability, and TOC) evolution in the Cline shale of the Midland Basin with the goal of elucidating general principles that can inform models for hydrocarbon exploration in fine-grained sedimentary systems.

GEOLOGICAL BACKGROUND

The Cline shale (Wolfcamp D) was deposited in the Midland Basin, an epicratonic foreland basin of the Ouachita orogenic belt and the eastern secondary subsidence tectonic unit of the greater Permian Basin (Figure 1; Yang and Dorobek, 1995). During the Late Pennsylvanian, a time of accelerated subsidence of the Midland Basin, deposition of the Cline shale occurred in the basin, and the Cisco and Canyon Groups of mixed siliciclastic–carbonate composition took place on the Eastern shelf and adjacent area (Wright, 2011; Baumgardner et al., 2016). Since 2009, the Cline shale has been drilled as an unconventional oil reservoir and has been considered as a secondary target in developing the Midland Basin unconventional resource plays (Roush, 2015). For operational purposes, the petroleum industry has long referred to the Cline shale as the Wolfcamp D interval.

Figure 1. Map of the Midland Basin showing the distribution of the Cline shale, general structural features, location of cores, and regional cross section. Map modified from Wright (2011) and Baumgardner et al. (2016). Bold, dotted black lines are the boundary of tectonic unit. CBP = Central Basin platform; DB = Delaware Basin; ES = Eastern shelf; HA = Horseshoe atoll; MA = Matador arch; MB = Midland Basin; NM = New Mexico; NWS = Northwest shelf; OA = Ozona arch; SC = Sheffield channel; TEX = Texas.

The Cline shale of the Midland Basin is underlain by Strawn carbonates and overlain by Wolfcamp strata (Figure 2) and has a thickness ranging from 200 to 425 ft (60 to 130 m) (Roush, 2015). Published structure maps indicate that the Cline shale dips westward (Baumgardner et al., 2016). The Cline shale is bounded by the Eastern shelf to the east, the Central Basin platform to the west, the Ozona arch to the southwest, and the Horseshoe atoll to the north (Figure 1). These four distinct boundaries make the Cline shale a relatively restricted depositional unit.

Figure 2. General stratigraphy of the Upper Pennsylvanian to lower Permian section in the Midland Basin. Location of the section was shown in Figure 1. Top of Strawn Formation carbonate is used as datum. Horizontal red lines represent formation boundary. Jagged black lines represent well logs. GR = gamma ray in API units; RES = resistivity in ohm-meters; SON = sonic in microseconds per feet.

During sea-level highstand, sediment input to the basin comprised dominantly a combination of platform-derived wackestone, pelagic calcareous mudrocks, and fine-grained siliciclastics, primarily comprising windblown clay (Brown et al., 1990). By contrast, during sea-level lowstand, platforms were exposed, and siliciclastic sediment-transport systems extended across the wide platform and input directly into the basin (Brown et al., 1990). The Wichita Mountains and the Arbuckle–Criner Hill uplift to the north of the basin provided terrigenous clastics to the basin and the Ouachita orogenic belt to the east of the Eastern shelf is another important clastic source area (Brown et al., 1990).

Global plate reconstructions by Blakey (2003) suggested that during the Late Pennsylvanian, the Midland Basin occupied a narrow inland seaway (Great Permian seaway) bounded by the Laurussian continent to the north and Gondwana to the south. Water circulation in the Midland Basin was restricted by stratification (development of both a thermocline and chemocline), forming the bottom anoxic environment (Algeo and Heckel, 2008). Water depths across the southern Midland Basin are difficult to estimate. Algeo and Heckel (2008) suggested that bathymetric variation in the Permian Basin region during the Late Pennsylvanian was considerable, with deep basins (hundreds of meters) separated by shallower sills that formed over structural highs. This range of water depth is similar to the early Permian Wolfcamp basinal setting in the Midland Basin, which is estimated to be 1000–2000 ft (300–600 m; Baumgardner et al., 2016).

SAMPLING AND ANALYTICAL METHODS

The four cores from the southern Midland Basin used in this study are located in Sterling, Reagan, Glasscock, and Martin Counties (Figure 1). The core from the Horwood 2151-H well is continuous (273 ft [83 m] in total) and penetrates through the whole Cline shale (Figure 2). The Greer O. L. 2, Glass G. W. 3-B, and Powell E. L. 1 wells are cored only in several short intervals (Figure 2). All of these cores are stored at the Core Research Center, Bureau of Economic Geology, The University of Texas at Austin.

Figure 3. Simplified core description of Horwood 2151-H with sample locations. Mudrock terminology used here is modified from Lazar et al. (2015). Left-point arrows indicate the direction of increasing grain size. ID = identification number.

In total, 140 samples were taken from four wells to prepare polished thin sections. Among these 140 samples, 35 were chosen for systematic bulk mineralogy x-ray diffraction (XRD) analysis, TOC analysis, field-emission scanning electron microscopy observation, whole-rock elemental analysis by x-ray fluorescence (XRF), and porosity and permeability measurement (using the Gas Research Institute [GRI] method; Guidry et al., 1996). For these 35 chosen samples, the Horwood 2151-H well was sampled in detail (32 samples) to assess mudrock heterogeneity in grain assemblages, petrophysical properties, and geochemical properties (Figure 3); the other 3 samples are from the remaining three wells (Table 1). The following were used as sampling criteria: (1) volumetrically significant major and minor lithologies and (2) material that is as homogeneous as possible within the individual sampling intervals (<2 in.) so that the different types of analyses made on subsamples can be correlated.

Bulk Composition Analysis

Element analyses were undertaken using Bruker Elemental Tracer IV-SD energy-dispersive XRF equipment. The XRF spectra for major elements were generated under vacuum using a rhodium (Rh) tube set at 15 kilovolts (kV) and 34.4 microampules (μA) for a count time of 60 s. The XRF spectra for trace elements were analyzed at 40 kV and 25 μA, with an Al-Ti-copper (Cu) filter on the equipment and a count time of 60 s. Core samples were analyzed by placing the flat slab side down on the nose of the instrument. Calibration during and after measurement rigorously followed the workflow proposed by Rowe et al. (2012).

The XRD, TOC, and GRI’s crushed-rock porosity and permeability measurement were completed by FireWheel Energy LLC (Houston, Texas). X-ray patterns of the sample powders (∼500 mg) are recorded on a Bruker D8 Advance powder x-ray Diffractometer using Cu radiation (40 kV and 100 milliampules) from a long line focus tube, a graphite monochromator in the diffracted beam, and a vacuum device to minimize absorption of the x-rays by air. Identification of minerals is made using EVA software (Bruker AXS Inc.) by comparison to reference mineral patterns archived in the Powder Diffraction Files of the International Centre for Diffraction Data. The XRD results are given as weight percentage. These analytical data were previously reported in the appendix of Zheng (2016).

Imaging Technology

Uncovered polished thin sections of approximately 25 μm thickness were produced for optical microscopy and scanning electron microscope (SEM) imaging. Samples were first inspected using conventional petrographic microscopy and were then coated with approximately 25 nanometers carbon (C) before being examined in the Field Electron and Ion Nova NanoSEM 430 field emission-SEM. All 35 samples were examined using both secondary electron (SE) and backscattered electron (BSE) modes. Elemental and mineral composition was identified by x-ray energy-dispersive spectroscopy (EDS) mapping. A unified scheme of false color was applied to the major mudrock elements to discriminate minerals: potassium (K) (yellow; K-feldspar, muscovite, and K-clay); silicon (red; quartz); sodium (Na) (aqua; Na-feldspar); magnesium (Mg) (fuchsia; dolomite, chlorite); calcium (Ca) (blue; calcite); iron (yellow; pyrite); and C (orange; OM). Twin 30-mm2 Bruker XFlash silicon drift detector EDS detectors were equipped using 15 kV accelerating voltage, 5.0 μm spot size, 30 μm aperture, a working distance of approximately 9–10 mm, and more than 500 s scanning time. Cathodoluminescence (CL) imaging using a Gatan ChromaCL detector was conducted on some specific samples to distinguish authigenic quartz and detrital quartz. The CL imaging was performed using 15 kV accelerating voltage, 5.0 μm spot size, 40 μm aperture, a working distance of approximately 12–13 mm, and 10 min of scanning time. The EDS maps were mixed with BSE maps, and the CL maps were mixed with the SE signal to create the images presented in this study.

Point-Count and Grain-Tracing Methods

A grain-assemblage point count was conducted on EDS maps using the image analysis program JMicrovision© (Roduit, 2008). The EDS mapping was performed at magnifications of 2500× to 3000× for all samples in this study. This is because we can confidently identify detrital silt particles at these magnifications. Areas having anomalously large allochems (commonly extra large, robust molluscan skeletal and agglutinated foraminifera) were intentionally avoided. Two images were taken of each sample to obtain a 200 × 200 μm2 area, which we believe approaches the representative elementary area suggested for mudrocks in previous studies (Yoon and Dewers, 2013; Houben et al., 2014; Kelly et al., 2016). For each image, 200 random points were counted (a total of 400 points for each sample).

Particle-size determination for the silt fraction (grain size between 4 and 9 ϕ or 63 and 2 μm) was performed on BSE images within the area of point counting. A boundary of 2 μm is used in this study to distinguish silt-size particles and clay-size particles. This is because we can confidently identify detrital particles of 2-μm diameter under SEM magnifications of 2500× to 3000×. Grain outlines were manually traced using the image analysis program JMicrovision (Roduit, 2008). Grain size is expressed as equivalent circular diameter (ECD), which by definition is the diameter of a circle having the same area as that of the object. All grains greater than 2 μm (>0.00008 in.) or 9 ϕ, except authigenic crystals, which were fully within the field of view, were included in the measurement. Mean grain size data from these all-grain images were corrected to standard volume-weighted mean grain size based on the grain area fraction (individual grain areas are normalized to total grain area, a proxy for volume).

RESULTS

Bulk Composition and Lithology

Bulk composition analysis data in this study, including XRF, XRD, TOC, porosity, and permeability, are given in Table 1 and the Appendix (supplementary material available as AAPG Datashare 120 at www.aapg.org/datashare). Clay minerals are the most important component in the Cline shale, ranging from 4 to 61 wt. % (mean of 40 wt. %; Table 1). Excluding kaolinite (authigenic pore filling) and chlorite (also dominantly authigenic), the average content of probable detrital clay (reported as smectite, illite, and mixed-layer illite–smectite in Table 1) is approximately 36 wt. %, ranging from 4 to 53 wt. %. Pore-filling crystalline illite can also be identified locally. Quartz is another important mineral in the Cline shale, ranging from 3 to 66 wt. % (mean of 34 wt. %). Carbonate minerals, including calcite, dolomite, ankerite, and siderite, are abundant in only three samples (i.e., samples 15, 39, and 54) of the wackestone and calcareous mudrock facies (Table 1). Excluding these three carbonate samples, calcite is detected in all but four of the samples, averaging approximately 3 wt. % and ranging from below detection to 20 wt. %, whereas dolomite and ankerite range from below detection to 8 wt. % (mean of 2 wt. %) and below detection to 4 wt. % (mean of 1 wt. %), respectively. Feldspars, including plagioclase and K-feldspar, are also important components, averaging 9 wt. % and ranging from below detection to 17 wt. %. Pyrite ranges from below detection to 10 wt. % (mean of 4 wt. %). Other minor minerals detected by XRD include siderite, barite, and apatite (Table 1).

Figure 4. Textural variations observed in backscattered electron images. Images for samples 20, 48, 61, and 84 illustrate variations in silt and sand content. Data obtained from JMicrovision (Roduit, 2008). The four samples selected represent important textural variations: sample 84 contains the finest mean silt size (8.35 ϕ); sample 61 contains the least silt (10.2%) but has a coarser mean grain size than sample 84; sample 48 contains abundant silt and also sand-size particles; sample 20 contains the highest silt content (31.6%). Examples of silt- and sand-size particles are labeled “s” in each image. Detrital dolomite (labeled “d”) with ankerite rim (red arrow), ankerite (labeled “a”), pyrite (labeled “py”), and silt-size micas (labeled “m”) are also observed in some samples. The red dashed line boxes highlight regions rich in clay-size matrix.

The lithofacies nomenclature of mudrocks used in this study is modified from the compositional classification proposed by Lazar et al. (2015). Mudrocks dominated by quartz; carbonate (e.g., calcite, dolomite, etc.); or clay minerals (e.g., illite, smectite, etc.) are named “siliceous mudrock,” “calcareous mudrock,” and “argillaceous mudrock,” respectively. Based on the XRD analysis of 15 mineral compositions (Table 1) and petrographic observations (described below), 4 lithologies were recognized: siliceous mudrocks, calcareous mudrocks, argillaceous mudrocks, and wackestone (Figure 3; Table 1). The TOC varies significantly, even for the same lithofacies over short vertical distances. Measured TOC ranges from 0.13 to 8.32 wt. % with a mean value of 3.48 wt. % (Table 1).

Textural Variation

All of the samples examined in this study are composed of clay- and silt-size grains, except sample 48, which also contains a substantial amount of sand-size particles (19.6 vol. %). Silt plus sand content ranges from 10.2 to 44.6 vol. % (Table 2). The corrected mean ECD of silt and sand grains ranges from 4.04 to 8.35 ϕ. The ϕ standard deviation ranges from 0.39 to 1.07, which suggests a wide range of grain sorting. Some examples of end-member textures of the silt- and sand-size particle distribution pattern are shown in Figures 4 and 5. Based on the textural classification of Macquaker and Adams (2003), all of the samples belong to silt-bearing clay-rich mudstone, except sample 48, which is sand- and silt-bearing clay-rich mudstone (Table 2).

Figure 5. Variations in the particle-size distribution of the four samples in Figure 4.

Major Extrabasinal Grains

In general, extrabasinal particles include detrital quartz, feldspar, lithic fragments, mica, and terrigenous OM (Figures 6). Detrital silt-size quartz is very common in most of the Cline shale. Detrital quartz is characterized by its angular shape (Figures 6). Figures 7 shows the most common reddish CL color of silt-size detrital quartz. Some specific silt-size detrital quartz can exhibit CL color from dark red to bright blue (Figure 7C, D). Some fabrics, such as microfractures and overgrowth zones of detrital quartz, can also be identified by CL (Figure 7C, D).

Figure 6. Major extrabasinal components observed in x-ray energy-dispersive spectroscopy mapping, sample 34. Silt-size detrital quartz, K-mica, Mg-mica, albite, and K-feldspar are abundant in rocks. The dominant clay mineral is K rich. Bulk x-ray diffraction analysis data indicate that this clay may most likely be a mixed layer of illite–smectite and illite. BSE = backscattered electron.

Detrital silt-size feldspar includes K-feldspar and albite (Figures 6). The most common lithic grains are quartz-feldspar aggregates, which may correspond to plutonic rock fragments (Folk, 1980; K. L. Milliken et al., 2017) (Figures 6). Monocrystalline micas include K-rich mica (muscovite) and Mg-rich mica (chlorite) (Figures 6).

Figure 7. Representative extrabasinal detrital quartz in the Cline shale. (A) X-ray energy-dispersive spectroscopy map of agglutinated foraminifera (dark-blue dashed line); sample 37. (B) Cathodoluminescence image of a close-up area in (A). Detrital quartz exhibits a reddish color. White arrows indicate quartz cement. (C) Cathodoluminescence image of detrital quartz shows cathodoluminescence color range from dark red to bright blue. White arrows indicate quartz cement; sample 48. (D) Cathodoluminescence image of detrital quartz shows cathodoluminescence color range from dark red to bright blue. The white arrow indicates quartz cement (dark-blue color); sample 83. BSE = backscattered electron.

A component of terrigenous OM (woody material characterized by particle shapes that reflect the cell structure typical of woody material) is present in the silt- and sand-size fraction (Figure 8A), but the volume of this material is relatively minor compared to other OM types (refer to next section).

Figure 8. Organic matter types identified in the Cline shale. (A) Organic matter particle of likely terrigenous origin (white arrow), sample 63. (B) Possible algal spore (white arrow); sample 43. (C) Possible algal spore (white arrow) partially collapsed by compaction, sample 12. (D) Migrated bitumen (white arrow), sample 47. det = detector; det BSED = backscattered electron detector; HFW = horizontal field width; HV = accelerating voltage; mag = magnification; spot = spot size; WD = working distance.

The dominant clay mineral is K rich (Figures 6). Bulk XRD analysis data indicate that this clay may most likely be a mixed layer of illite–smectite and illite.

Three carbonate samples (i.e., samples 5, 15, and 39) have experienced heavy diagenesis overprinting; thus, the original grain assemblage cannot be identified with precision. As a result, little information of grain assemblage can be obtained from them. Except for carbonate samples, extrabasinal grains account for approximately 87.5 vol. % of total grains, ranging from 69.5 to 98.5 vol. % on the basis of point count (Appendix, supplementary material available as AAPG Datashare 120 at www.aapg.org/datashare).

Figure 9. Representative intrabasinal grains in the Cline shale. (A) X-ray energy-dispersive spectroscopy map showing sponge spicule, sample 59; (B) x-ray energy-dispersive spectroscopy map showing radiolaria (replaced by ankerite) and pore-filling kaolinite, sample 39; (C) agglutinated foraminifera (AF) (dashed blue line), backscattered electron (BSE) image, sample 2; (D) x-ray energy-dispersive spectroscopy map showing molluscan skeletal fragment, sample 34; (E) AF (partly replaced by pyrite) and organomineralic aggregates (OMAs) (dashed blue line), BSE image, sample 1; and (F) x-ray energy-dispersive spectroscopy map showing plausible Ca-phosphate peloids (arrows), sample 35. det = detector; det BSED = backcattered electron detector; HFW = horizontal field width; HV = accelerating voltage; mag = magnification; spot = spot size; WD = working distance.

Major Intrabasinal Grains

Criteria for identification of intrabasinal grains follow Scholle and Ulmer-Scholle (2003). Intrabasinal grains are identified based on their size, shape, internal structure, mineral composition, and age range. Major intrabasinal particles observed under the SEM include biosiliceous allochems (sponge spicules and radiolarians; Figure 9A, B); agglutinated foraminifera (Figure 9C), biocalcareous allochems (Figure 9D); OMAs (Figure 9E); Ca-phosphate peloids (Figure 9F); and intraclasts (phosphatic grains, vertebrate bones and teeth, and glauconite; Figure 10).

Figure 10. Representative intraclasts in the Cline shale. (A) Phosphatic grains (black arrows) occur with detrital silt quartz, suggesting reworked deposition, transmitted light, sample 61; (B) phosphatic-coated grain (yellow arrows), massive skeletal fragment of a shallow-platform dweller suggests downslope transportation, transmitted light, Horwood 2151-H, 7991.1 ft; (C) locally abundant glauconite (green), transmitted light, Glass G. W. 3-B, 10,402.9 ft; and (D) vertebrate bone, transmitted light, Horwood 2151-H, 7982.7 ft.

Abundant siliceous allochems (sponge spicules and radiolarians) are common in siliceous mudrocks. The CL color of sponge spicules (Figure 11A, B) is pale mauve to purple and is generally of low intensity compared to that of extrabasinal detrital quartz (Figures 7). Radiolarians have been replaced by calcite, dolomite, or ankerite in the Cline shale, but we can still identify them based on the size and shape of allochems. Flattened tests of benthic agglutinated foraminifera are present in the Cline shale and are always associated with OM-rich intervals and siliceous mudrock. In some cases, benthic agglutinated foraminiferal mats were identified (Figure 9C).

Figure 11. Representative intrabasinal quartz in the Cline shale. (A) X-ray energy-dispersive spectroscopy map of sponge spicules (dashed-line box), sample 59. (B) Cathodoluminescence image of a close-up area in (A); sponge spicules (white arrows) show low cathodoluminescence intensity and pale-mauve to dull-reddish cathodoluminescence color. (C) X-ray energy-dispersive spectroscopy map of euhedral quartz replacement of unknown skeletal fragment, with authigenic Ca-phosphate and kaolinite filling in the primary intragranular pore, sample 19. (D) Same area as seen in (C) but under cathodoluminescence imaging; euhedral quartz shows low cathodoluminescence intensity and pale-mauve cathodoluminescence color. (E) X-ray energy-dispersive spectroscopy map showing quartz cement in an intragranular pore within primary planktonic organic matter, sample 37. (F) Same area as seen in (C) but under cathodoluminescence imaging; pore-filling quartz cement shows low cathodoluminescence intensity and pale-mauve cathodoluminescence color. BSE = backscattered electron.

Biocalcareous allochems consist mainly of mollusks, crinoids, echinoids, and fusulinids (Figure 9D, B). These benthic allocohems commonly have robust skeletal fragments and are distributed randomly through the sediment. Most of the biocalcareous allochems are observed in wackestone and calcareous mudrocks. Molluscan skeletal fragments are also observed in argillaceous mudrocks. In general, no biocalcareous allochems are observed in siliceous mudrocks.

The OMA (Figure 9E), Ca-phosphate peloids (Figure 9F), phosphatic grains (Figure 10A, B), and glauconite (Figure 10C) are commonly observed in siliceous mudrocks and are commonly associated with high TOC.

Possible algal spores with distinctive shapes indicate marine sources (Figure 8B, C). Organic particles in the lower end of the silt range that lack distinctive shapes cannot be readily identified as terrestrial kerogen, marine kerogen, or secondary migrated OM.

Except for carbonate samples 5, 15, and 39, intrabasinal grains constitute approximately 7.6% of total grains, ranging from 0.3 to 23.3 vol. % on the basis of point count (Appendix, supplementary material available as AAPG Datashare 120 at www.aapg.org/datashare).

Diagenetic Features

Three carbonate samples (samples 5, 15, and 39) include microcrystalline dolomite. The authigenic components (mainly dolomite and ankerite crystals) from these three carbonate samples (by point count) range from 42.5 to 88.6 vol. %, with an average of 69.4 vol. % (Appendix, supplementary material available as AAPG Datashare 120 at www.aapg.org/datashare). The heavy diagenetic overprinting makes the original grain assemblage difficult to identify. One thing that should be noted here is that the XRD data for sample 5 suggest only 3 wt. % of dolomite and ankerite in this sample (Table 1). However, abundant dolomite and ankerite crystals were identified under SEM observation (10 and 32.5 vol. % by point count, respectively; Appendix, supplementary material available as AAPG Datashare 120 at www.aapg.org/datashare). This huge difference may arise from the large compositional heterogeneity across subsamples in the gravity-flow wackestone facies. Authigenic components obtained from other siliciclastic samples (by point count) range from 0.5 to 10.3 vol. %, with an average of 5 vol. % (Appendix, supplementary material available as AAPG Datashare 120 at www.aapg.org/datashare). Diagenetic features observed in siliciclastic samples include quartz overgrowths, clay-size microquartz cement, Ca-phosphate cement, pore-filling migrated OM, grain replacement, euhedral dolomite and ankerite, and pyrite framboids. In most samples, chemical diagenetic features observed by SEM tend to exhibit spatial localization. For example, some minerals tend to nucleate on specific grains (e.g., quartz overgrowths) or in specific locations (e.g., only in large pores). Some localized diagenetic features (e.g., phosphatic nodules and carbonate concretions) can be observed at multiple scales from cores to thin sections.

Grain Replacement

In the Cline shale, radiolarians and sponge spicules, originally made of opal (Scholle and Ulmer-Scholle, 2003), are now replaced by crystalline quartz, calcite, albite, ankerite, and pyrite (Figures 9A, B; 11A; 12). Euhedral quartz replacement of some allochems of unknown taxonomy are very common in siliceous mudrocks (Figure 11C). The pale-mauve to dull-reddish CL of quartz replacement (Figure 11B, D) is generally of low intensity compared to that of extrabasinal quartz (Figures 7). Some larger sponge spicules display distinct stripes of contrasting CL color and intensity. Mollusk fragments, originally aragonite in general (Scholle and Ulmer-Scholle, 2003), are replaced by calcite, quartz, and albite (Figure 12C). In addition, chalcedony replacement of calcite skeletal fragments is observed locally.

Figure 12. Authigenic minerals in the form of grain replacements and cement. (A) Sponge spicules are replaced by calcite and have authigenic quartz filling their central canals, sample 34; (B) sponge spicules are made mostly of quartz but are partially replaced by albite, sample 54; (C) molluscan skeletal fragment (formerly aragonite) is now partially replaced by quartz and albite, sample 34; (D) sponge spicule is replaced by pyrite and has authigenic kaolinite filling its central canal, sample 63. BSED = backscattered electron detector; HFW = horizontal field width; HV = accelerating voltage; mag = magnification; spot = spot size; WD = working distance.

Quartz Cement

Quartz cement can be observed on detrital quartz grain surfaces (Figure 7B, C), agglutinated foraminifera (Figure 7B), and in primary intragranular pores (Figure 11E, F). Quartz cement is volumetrically minor and is observed locally at contacts between quartz grains because abundant detrital clays have compacted to reduce intergranular pores, causing limited space for syntaxial quartz cement growth (Figure 7B). Quartz cement in agglutinated foraminifera is more commonly observed in the Cline shale (Figure 7B). Authigenic pore-filling quartz is also observed in intragranular pores within primary planktonic OM (Figure 11E, F). The most abundant form of authigenic quartz however is in the form of weakly luminescence 1–3 μm crystals that are distributed through the clay-size matrix in siliceous mudrock samples (Figure 13). An SEM observation under 6000× to 8000× magnification revealed quartz in the clay-size fractions. In the case of sample 59 (abundant in sponge spicules; Figure 13), quartz in the clay-size fraction is abundant (Figure 13A). The CL imaging (Figure 13B) again confirms that this clay-size quartz has a dull-reddish to mauve luminescence similar to the siliceous sponge spicules shown in Figure 11B. Clay-size microquartz is also observed in sample 63 (a relatively fine-grained and siliceous sample; Figure 13C, D) and is believed to be intrabasinal based on the dull-reddish to mauve luminescence.

Figure 13. Clay-size microquartz in representative samples. (A) X-ray energy-dispersive spectroscopy image showing silt-size quartz (red), albite (aqua), and calcite (dark blue) within a matrix that is dominantly clay-size microquartz (red) and clay minerals (green); sample 59. Mapped elements were chosen to discriminate the listed minerals. Note that the colors displayed on the maps do not correspond exactly to the colors shown in the element key because these minerals contain other elements in addition to the one mapped. (B) Enlarged area of dashed white-line box as seen in (A) shows silt particles with bright and dark luminescence in a matrix of dark luminescing clay-size microquartz and clay minerals, cathodoluminescence image. White arrows denote quartz cement on silt-size detrital-quartz surface. Yellow ovals highlight the clay-size microquartz with low cathodoluminescence intensity and pale-mauve cathodoluminescence color. (C) X-ray energy-dispersive spectroscopy image showing silt-size quartz (red), albite (aqua), and calcite (dark blue) in a matrix that is dominantly clay-size microquartz (red) and clay minerals (yellow); sample 63. (D) Enlarged area of dashed white-line box as seen in (C) shows silt particles with bright and dark luminescence in a matrix of dark luminescing clay-size microquartz and clay minerals, cathodoluminescence image. White arrows denote quartz cement on silt-size detrital quartz surfaces. Yellow ovals reveal clay-size microquartz with low cathodoluminescence intensity and pale-mauve cathodoluminescence color. BSE = backscattered electron.

Euhedral Dolomite and Ankerite

Ankerite and dolomite in the form of silt-size euhedral crystals with an oddly mottled fabric are commonly observed in the Cline shale (Figure 14A–C). The ankerite crystals in Figure 14A have an intergrown relationship.

Figure 14. Euhedral ankerite and plausible matrix-dispersed Ca-phosphate cement. (A) Backscattered electron (BSE) image of ankerite (arrows), sample 59. (B) Same area as seen in (A) under x-ray energy-dispersive spectroscopy map showing ankerite (arrows). (C) Euhedral ankerite (white arrows), sample 4. The euhedral ankerite is plausibly displacive. (D) Plausible matrix-dispersed Ca-phosphate cement, sample 63. Calcite- and dolomite-replaced radiolaria is labeled “R.” det = detector; det BSED = backscattered electron detector; HFW = horizontal field width; HV = accelerating voltage; mag = magnification; spot = spot size; WD = working distance.

Calcium-Phosphate Cement

Localized zones of Ca-phosphate cementation (Figure 14D) are also common in the Cline shale. Syndepositional Ca-phosphate cements (K. L. Milliken and Day-Stirrat, 2013) occupy large pores before they were compacted, forming pervasive cements as shown in Figure 14D.

Precipitates in Anomalously Large Pores

Authigenic precipitates in the anomalously large intragranular pores (up to 100 μm in diameter) of rare fossil fragments were observed. The most common authigenic minerals in such pores are Ca-phosphate and kaolinite (Figures 11C, D; 12D).

Pyrite Framboids

Pyrite framboids are present in all facies, although they are much more common in mudrocks than in wackestone. Grain-tracing measurements of framboids (under SEM) reveal that the average diameter of pyrite framboids ranges from 1.7 to 7.3 μm. Specifically, abundant small-size framboids are observed in siliceous mudrocks (average size <4 μm); however, the average size of pyrite framboids in other facies is greater than 4 μm.

Migrated Organic Matter

Pore-filling solid hydrocarbon was observed within intergranular pores and fractures (Figure 8D). The pore-filling and nonparticulate character shown in Figure 8D are two typical features of migrated OM under SEM (Loucks and Reed, 2014).

Petrophysical Properties and Their Relationships with Textural Variation and Mineral Compositions

The GRI crushed-rock porosity (as-received gas-filled porosity) and permeability of the Cline shale range from 0.46 to 3.29% (mean of 1.59%) and 4.7 × 10−5 to 2.9 × 10−4 md (mean of 1.2 × 10−4 md; Appendix, supplementary material available as AAPG Datashare 120 at www.aapg.org/datashare), respectively. Figure 15A shows a crossplot of GRI crushed-rock porosity versus GRI crushed-rock permeability. A strong positive correlation exists between porosity and permeability (coefficient of determination [R2] = 0.8). In addition, crossplots of TOC versus GRI crushed-rock porosity and TOC versus GRI crushed-rock permeability also suggest a weakly positive linear relationship (Figure 15B, C).

Figure 15. (A) Permeability versus porosity by the Gas Research Institute (GRI) crushed-rock method; (B) porosity versus total organic carbon (TOC); (C) permeability versus TOC. Mudrock terminology used here is modified from Lazar et al. (2015). See Figure 3 for core description and sample location. Reservoir properties (porosity, permeability, and TOC) do not display significant correlations with lithofacies (mineral composition). Black lines are regression line. R2 = coefficient of determination.

The positive relationship between porosity, permeability, and TOC may be related to the abundant OM pores in the Cline shale (Reed and Roush, 2016). However, reservoir properties are rarely correlated to textural variation and mineral composition. For example, samples 83 and 70 have very similar silt content (12% vs. 12.8%; Table 2), mean silt size (7.52 vs. 7.6 ϕ), and grain sorting (0.48 vs. 0.5 ϕ); however, sample 83 is TOC poor (0.56%), whereas sample 70 is TOC rich (7.37%). In addition, samples 83 and 19 exhibit very similar bulk mineral compositions (27% vs. 26% for quartz, 11% vs. 14% for feldspar, and 51% vs. 50% for clay, respectively; Table 1); however, the TOC of sample 19 is 7.93%, far richer than sample 83 (TOC = 0.56%). In the Cline shale, samples with similar textural variations and bulk mineral compositions may show great variations in reservoir properties (porosity, permeability, and TOC).

DISCUSSION

Difficulties with Mineral Composition and Lithological Characterization

The extremely fine-grained particles in mudrocks are inherently difficult to accurately describe compositionally based on core descriptions and well-log curves. In this study, lithologies were first characterized by mineral composition (XRD) (Figure 3; Table 1) as suggested by Lazar et al. (2015). However, Figure 15 suggests that reservoir properties (porosity, permeability, and TOC) do not display significant correlations with lithofacies classification based on mineral content (i.e., quartz, clay, and carbonate minerals). A more detailed and accurate composition classification (Macquaker-style classification; Macquaker and Adams, 2003) based on XRD was also introduced in this study to test the relationship between reservoir properties and mineral composition (Table 1). However, the Macquaker-style classification carried almost no significant information about reservoir properties in the Cline shale. For example, samples 35 and 50 have a very similar XRD mineral composition, and both belong to feldspar-, quartz-, and clay-bearing mudrocks based on the Macquaker-style classification (Table 1); however, these two samples show very different porosity (2.33% vs. 1.14%), permeability (1.9 × 10−4 vs. 7.5 × 10−5 md), and TOC (7.29 vs. 0.97 wt. %) (Table 1). In addition, variations in texture (e.g., variation in silt content) are too small to make a difference based on the classification proposed by Macquaker and Adams (2003). As shown in Table 2, all of the samples belong to silt-bearing clay-rich mudstone, except sample 48, which is sand- and silt-bearing clay-rich mudstone. In this situation, neither textural variations nor mineral compositions alone are sufficient to confidently decipher variations in porosity, permeability, and TOC.

Figure 16. Bulk mineralogy from x-ray diffraction (XRD) versus point count of key components in the Cline shale. (A) Quartz. (B) Feldspar. (C) Clay minerals. Black line indicates 1:1 line.

Previous studies have suggested that variations in nonclay minerals in the clay-size fraction have an important effect on the reservoir properties of mudrocks (e.g., Storvoll et al., 2005; Thyberg et al., 2010; K. L. Milliken et al., 2012a, 2018; Fishman et al., 2013, 2015; Gale et al., 2014; Milliken and Olson, 2017). The average bulk quartz content of the Cline shale, based on XRD, is 34 wt. %. This bulk measurement incorporates quartz of detrital and authigenic origins. The point-count quartz volume content (mean of 24 vol. %), which we can confidently use to identify this upper clay-size to silt-size quartz, is less than the bulk XRD quartz content (Figure 16A). Average values for feldspar content (albite + K-feldspar) are 6 vol. % by point count and less than XRD bulk feldspar weight content (mean of 9 wt. %; Figure 16B<). However, average values for clay content are 49 vol. % by point count (including mica) and are higher than XRD clay content (mean of 40 wt. %; Figure 16C). Such results suggest that the petrographic data are counting certain nonclay mineral (e.g., poorly resolved clay-size feldspar or quartz) as clay-size matrix. This inference is further supported by observed clay-size microquartz in Figure 13. Despite the fact that XRD data are given in weight percentage, whereas SEM petrographic textural analysis is a volume percentage, the densities of these minerals are similar enough to bulk density that this comparison is reasonable and informative (K. L. Milliken et al., 2012a). Such significance of nonclay minerals in the clay-size fraction was also revealed in other marine mudrock systems, such as the Mississippian Barnett Formation and the Cretaceous Eagle Ford Group (Bunting and Breyer, 2012; K. L. Milliken et al., 2016). K. L. Milliken et al. (2016) reported that the average quartz content from XRD is 14.7 wt. % for the Eagle Ford Group; however, the average point-count quartz content is only 2.1 vol. % for these same samples (see their figure 14B). These data suggest that only 14 vol. % of the total quartz in rocks was identified and accounted for by the point-count method in the Eagle Ford Group. Bunting and Breyer (2012) suggest that the quartz content from XRD ranges from 25 to 70 wt. % for the Barnett Formation, whereas the point-count quartz content for these same samples only ranges from 0 to 25 vol. % (see their figure 10A).

Interpretation of Grain Sources

Point-count results indicate that extrabasinal detrital components account for approximately 82.6% volume of total rocks, ranging from 11.4 to 98.5 vol. % (Appendix, supplementary material available as AAPG Datashare 120 at www.aapg.org/datashare). Most of these extrabasinal components are mica, detrital quartz, feldspar, lithic fragments, and clay minerals. They were most likely brought into the basin through fluvial and deltaic systems or windblown hemipelagic fallout.

Common biocalcareous allochems identified in the Cline shale are benthic organisms such as robust mollusks, fusulinids, crinoids, and calcareous algae. They commonly occur in the wackestone, calcareous mudrocks, and argillaceous mudrocks. The presence of carbonate-platform shallow-water benthic allochems in the basinal mudrocks and wackestone indicates downslope transport from the Eastern shelf of the Midland Basin during a highstand. This depositional process also explains the mineral heterogeneity of sample 5 from gravity-flow wackestone facies. However, other benthic allochems, such as thin-walled mollusks, sponge spicules, and agglutinated foraminifera, are also identified in the Cline shale and are likely in situ infauna as suggested by Macquaker et al. (2010) and K. Milliken (2014). Fauna of this type are able to survive under basinal environments, even under conditions of extremely low oxygenation (Bernhard, 1993; Sen Gupta and Machain-Castillo, 1993).

Radiolarians, phosphatic allochems (conodonts and vertebrate bones and teeth), Ca-phosphate peloids, fecal pellets, algal spores, and OMAs are derived from the water column (Scholle and Ulmer-Scholle, 2003; Macquaker et al., 2010) and are highly related to surface productivity. These OMAs were interpreted as ancient examples of “marine snow,” which are associated with surface productivity and phytoplankton blooms (Macquaker et al., 2010, p. 939).

Impact of the Grain Assemblage on Diagenesis

It is clear that a high content of intrabasinal grains and authigenic cement, such as those observed in the Mississippian Barnett Formation and Cretaceous Eagle Ford Group, are not present in the Cline shale (Figures 6). K. Milliken (2014) suggests that 18%–42% volume content of the intrabasinal grain component and 12%–38% volume content of the authigenic cement are observed in the Mississippian Barnett Formation (see table 5 in K. Milliken, 2014). Additionally, in the Cretaceous Eagle Ford Group, 42%–49% volume content of the intrabasinal grain assemblages and 12%–16% volume content of the authigenic cement are observed (see table 5 in K. Milliken, 2014). Except for three samples from calcareous mudrock and wackestone facies (Figure 3), clay-mineral content by XRD ranges from 9 to 61 wt. % (mean of 43 wt. %). The abundance of ductile clay minerals suggests that the Cline shale has the potential for substantial compaction. Generally, low cement volumes and low total porosity (dominated by OM-hosted pores; Reed and Roush, 2016) suggest low intergranular volume, which implies that the Cline shale has experienced intense compaction. Direct petrographic indicators of compaction are seen as organic flakes (Figure 8B, ), agglutinated foraminifera (Figure 9C, E), OMAs (Figure 9E), and Ca-phosphate peloids (Figure 9F) that have been compacted to a squashed shape and aligned parallel to bedding. Compacted laminations are evident around some rigid grains (Figure 11C). Some laminations are highlighted by squeezed biota, organic flakes, or peloids. Thin, flat skeletal fragments tend to align during compaction.

The dominance of compaction is further supported by high-resolution CL imaging that documents the general absence of quartz cementation on the surfaces of detrital silt-size quartz particles in clay-rich rocks (Figure 7B). The minor amounts of quartz cement observed in agglutinated foraminifera and in the larger pores of some OM particles (Figure 11E, F) show that quartz cementation occurred, but surfaces of most silt-size quartz grains were covered by compacted clays prior to the onset of quartz cementation and thus were not available to nucleate quartz cement. Two factors appear to influence in the dominance of compaction in the Cline shale: (1) the general lack of chemically unstable biogenic allochems inhibits early intergranular cementation that can bind grain contacts and inhibit compaction, and (2) relatively clay-rich textures prevent silt particles from reaching a state of compaction at which they form a rigid grain pack that resists further compaction (Schneider et al., 2011). Because of limited early cementation and a lack of rigid grain packs, the principal cause of porosity reduction, beginning from the very high values characteristic of muds at the depositional sediment–water interface (near 70%–80%; Velde, 1996) to the very low values that characterize the Cline shale today (0.5%–3.3%), is compaction. However, some specific samples, such as samples 59 and 63, contain abundant sponge spicules and are very rich in silica. In these samples, we identified early clay-size microquartz cementation (Figure 13). Because such early cementation can resist compaction, these sponge spicule–rich samples generally have a higher porosity and permeability compared to these clay-rich rocks.

Based on SEM observation, Reed and Roush (2016) suggested that the porosity of the Cline shale is dominated by OM-hosted pores, whereas interparticle and intraparticle pores, which are common in the Eagle Ford Group, are limited in the Cline shale. This is because ductile clay minerals were squeezed into interparticle pores by compaction, and calcareous allochems, which comprise the most important intraparticle pores, are limited in most of the Cline shale rocks. Migrated diagenetic OM (solid residual bitumen) was observed both by Reed and Roush (2016) and in this study (Figure 8D). Emplacement of this diagenetic OM clearly further reduced the primary porosity.

Impact of the Grain Assemblage on Reservoir Properties

Textural controls (silt content) on reservoir properties are not observed in the Cline shale. Similarly, no specific relationship between textural variations and reservoir properties is observed in the Barnett Formation (K. L. Milliken et al., 2012a). This is because expected relationships have been erased by the combination of protracted compaction, cementation, and hydrocarbon migration (K. L. Milliken et al., 2012a).

As discussed earlier, grain assemblages dominated by terrigenous extrabasinal grains, biocalcareous allochems, and biosiliceous allochems arose from three distinct primary depositional settings, respectively. K. Milliken (2014) suggested that rocks dominated by any one of these three grain assemblages follow contrasting and predictable diagenetic pathways that have significant implications for the evolution of rock properties. Specifically, biosiliceous allochems are favored for planktonic OM enrichment and early cementation, whereas terrigenous extrabasinal grains cause detrital dilution of OM, and ductile clay minerals tend to compact (K. Milliken, 2014).

In the Cline shale, intrabasinal grains are composed mainly of biosiliceous allochems, Ca-phosphate peloids, and OMAs, whereas biocalcareous allochems are limited and identified mainly in wackestone and calcareous mudrocks, which are interpreted as gravity-flow deposits from the Eastern shelf (Hamlin and Baumgardner, 2012). We use the ratio of extrabasinal components to intrabasinal components (E/I) to characterize the Cline shale with respect to reservoir properties. As shown in Figure 17A, a very good negative linear relationship between E/I (in the logarithmic scale) and TOC (R2 = 0.86) suggests the effectiveness of E/I in evaluating TOC. However, linear relationships between E/I and porosity, as well as relationships between E/I and permeability, are not as good as the correlation between E/I and TOC (Figure 17B, C). This suggests that diagenetic processes probably resulted in petrophysical heterogeneity, even for samples with similar grain assemblages. Despite the fact that the negative relationships between E/I, porosity, and permeability (Figure 17B, C) are not so good, we can differentiate high-quality reservoirs from poor ones based on E/I. Specifically, there is an obvious threshold (E/I = ∼20), when E/I exceeds this value porosity and permeability decrease significantly (Figure 17B, C). Intrabasinal grains, especially the OMAs and Ca-phosphate peloids observed in the Cline shale, are commonly associated with high surface productivity and OM-rich layers (marine snow) (Macquaker et al., 2010). Marine planktonic OM developed during this high surface productivity period was transported quickly to the anoxic seafloor and formed OM-rich layers. In addition, pore systems in the Cline shale are developed mainly in OM (both kerogen and migrated bitumen; Reed and Roush, 2016); thus, high-TOC samples always correspond to high porosity and permeability (Figure 15). Compared to other organic-rich marine shales, such as the Mississippian Barnett Formation (E/I = 1.2–2.4; K. Milliken, 2014; see her table 5) and the Cretaceous Eagle Ford Group (E/I = 0.7–1.1; K. Milliken, 2014; see her table 5), the E/I ratio of the Cline shale is very high. The E/I ratio of the Cline shale is similar to that of the organic-rich lacustrine Triassic Yanchang Formation mudrocks, Ordos Basin, China, which range from 6 to 125 (K. L. Milliken et al., 2017; see their supplementary table 1).

Figure 17. Crossplot of ratio of extrabasinal grains to intrabasinal grains (E/I), nickel (Ni) content, and reservoir properties. (A) E/I versus total organic carbon (TOC); (B) E/I versus porosity; (C) E/I versus permeability; (D) Ni versus TOC; (E) Ni versus porosity; and (F) Ni versus permeability. Porosity and permeability decreased abruptly when they reach the E/I and Ni threshold. Black lines are regression line. GRI = Gas Research Institute; R2 = coefficient of determination.

We modified the grain assemblage classification of K. Milliken (2014) (see her figure 2) because an obvious reservoir property threshold occurred at E/I = approximately 20 (∼95% of terrigenous grains; Figure 17B, C). Ninety-five percent is regarded as the boundary of terrigenous–argillaceous mudrocks (“tarls”) and “biosiliceous tarl” (Figure 18). Based on this classification, samples from the Cline shale can be classified as biosiliceous tarl and tarl (Figure 18; Table 1). These two groups exhibit distinct reservoir properties as shown in Figure 19. Specifically, the TOC, porosity, and permeability of biosiliceous tarl is 6.1%, 2.1%, and 1.6 × 10−4 md, respectively; however, the average TOC, porosity, and permeability of tarl is only 1.3%, 1.1%, and 7.4 × 10−5 md, respectively (Figure 19).

Figure 18. Compositional classification for fine-grained sediments and sedimentary rocks (modified from K. Milliken, 2014). All 33 samples in this study are terrigenous–argillaceous (tarl) and biosiliceous tarl. The compositional classes of tarl and biosiliceous tarl are based on contrasts in the proportions of extrabasinal detrital quartz, feldspar, and clay versus intrabasinal components, notably calcareous and siliceous allochems. Area 1 represents a variation of Cretaceous Eagle Ford Group mudrocks in this diagram (K. Milliken, 2014; her figure 6). Area 2 represents a variation of Mississippian Barnett Formation mudrocks in this diagram (K. Milliken, 2014; her figure 6). Area 3 represents a variation of Triassic Yanchang Formation mudrocks, Ordos Basin, in this diagram (K. L. Milliken et al., 2017; their figure 13). The orange, blue, green, and yellow colors distinguish classifications from each other. Circles located near the top of the triangle are location of samples from this study in this diagram. Carl = calcareous–argillaceous; Sarl = siliceous–argillaceous.

Implications for the Identification of Favorable Unconventional Plays

As shown in Figures 17–19 and as discussed earlier, E/I and grain-assemblage classifications are effective for evaluating reservoir properties. However, quantifying grain assemblages from an SEM point count is time-consuming and practically impossible to do with the large quantity of samples required in industrial exploration. Energy-dispersive XRF analysis used in this study is a rapid and economic way (compared to inductively coupled plasma mass spectrometry and total loss on ignition analysis) to obtain elemental composition data from a flat core surface in the laboratory (Rowe et al., 2012). Elemental data from high-resolution energy-dispersive XRF analysis are very helpful to reveal inch-to-foot-scale alternation of paleoenvironments such as detrital input, redox conditions, and surface productivity (Rowe et al., 2012). Additionally, industry groups are trying to access XRF-based element data from cuttings at the well site while drilling shale wells in recent years (Tonner et al., 2012; Chok et al., 2014). This portable and field deployable XRF analytical technique will offer a more cost-effective and lower-risk alternative for reservoir characterization (Tonner et al., 2012; Chok et al., 2014).

Figure 19. Reservoir properties for lithologic groups by point counting of grain assemblage as shown in Figure 18. (A) Total organic carbon (TOC) and porosity; (B) permeability. GRI = Gas Research Institute; Tarl = terrigenous–argillaceous.

Nickel (Ni) is recognized as a proxy for planktonic OM because it is a micronutrient used by marine biota (Tribovillard et al., 2006). In addition, Ni is dominantly delivered to sediments in association with OM sinking flux (organometallic complexes) and is thus commonly used as a proxy for productivity (Tribovillard et al., 2006). Using Ni as a proxy for paleoproductivity has been widely applied in different hydrocarbon-producing shale systems, including the Wolfcamp shale (Baumgardner et al., 2016), Eagle Ford Group (Alnahwi et al., 2018), Yanchang Formation (Wang et al., 2017), and Cline shale in this study. Point-count intrabasinal grain content and XRF-based Ni content suggests a relatively good linear relationship (R2 = 0.59; Figure 20). The positive linear relationship between TOC and Ni (R2 = 0.67; Figure 17D) indicates that primary productivity is a major control on the TOC value. Thus, Ni content can be used as a proxy for TOC estimation when measured TOC is unavailable. In addition, 5% of intrabasinal grains (i.e., E/I = 20) corresponds to approximately 50 ppm of Ni according to the regression line shown in Figure 20. Both porosity and permeability increased abruptly when Ni content exceeded 50 ppm as shown in Figure 17E, F. Thus, Ni content can be used as a powerful parameter to help identify high-TOC, high-porosity, and high-permeability layers of the Cline shale during unconventional exploration.

Figure 20. Crossplot of x-ray fluorescence–based nickel (Ni) content and point-count intrabasinal grains content, suggesting a good linear relationship. R2 = coefficient of determination.

Other elemental proxies for paleoproductivity, such as phosphorus (P) and barium (Ba), do not show obvious relationships with TOC, porosity, permeability, and E/I in this study. This may be because P in sediments is likely to recycle back into water column; thus, P may be limited in sediments even with high surface water productivity (Tribovillard et al., 2006). Additionally, barite dissolves under strongly reducing, sulfate-depleted conditions, releasing Ba into interstitial pore water (Tribovillard et al., 2006). The element Cu also behaves as a micronutrient and shows similar enrichment pattern as Ni in mudrocks (Tribovillard et al., 2006). However, the relationships between Cu and reservoir properties (i.e., TOC, porosity, permeability, and E/I) are not as good as Ni in this study. This is likely caused by limited data points here or some specific depositional environments of the Cline shale that need further study.

CONCLUSIONS

This work examines how the primary composition of grain assemblages in mudrocks affect the postdepositional processes (diagenesis) that eventually determine rock properties (porosity, permeability, and

TOC

).

1. In general, grain assemblages in the OM-rich Cline shale are dominated by grains of extrabasinal derivation (11.4 to 98.5 vol. %; average volume of 82.6%). However, some specific silica-rich samples display significant variations in the proportions of extrabasinal and intrabasinal sources, and variations are manifested in both clay-size and silt-size grain components. Quartz in these samples occurs in both clay-size and silt-size fractions and is of both intrabasinal and extrabasinal origin.

2. Diagenetic features are most evident as grain replacements (including quartz, calcite, and pyrite), cements in large pores (up to 100 μm in diameter), euhedral ankerite, and localized Ca-phosphate cement. Abundant intergranular cements are observed only in samples rich in biosiliceous allochems. Most samples are rich in detrital clay minerals, and the dominant diagenetic process is compaction, which has caused a considerable loss of intergranular pores and overprinted the impact of texture (grain size, sorting) on the reservoir quality.

3. Rocks containing abundant intrabasinal grain assemblages have enhanced amounts of authigenic clay-size microquartz in the matrix and OM (both kerogen and migrated bitumen). A low E/I ratio suggests high TOC, high porosity, and high permeability in the sample.

4. The element Ni is recognized as a proxy for paleoproductivity and exhibits a positive relationship with intrabasinal grain content and reservoir properties (i.e., TOC, porosity, and permeability) in the Cline shale. The XRF-based Ni analysis is a rapid and cost-effective way to delineate favorable unconventional-play sweet spots for the Cline shale in unconventional exploration.

REFERENCES CITED

Algeo, T. J., and P. H. Heckel, 2008, The Late Pennsylvanian midcontinent sea of North America: A review: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 268, no. 3–4, p. 205–221, doi:10.1016/j.palaeo.2008.03.049.

Alnahwi, A., R. G. Loucks, S. C. Ruppel, R. W. Scott, and N. Tribovillard, 2018, Dip-related changes in stratigraphic architecture and associated sedimentological and geochemical variability in the Upper Cretaceous Eagle Ford Group in south Texas: AAPG Bulletin, v. 102, no. 12, p. 2537–2568, doi:10.1306/05111817310.

Aplin, A. C., and J. H. S. Macquaker, 2011, Mudstone diversity: Origin and implications for source, seal, and reservoir properties in petroleum systems: AAPG Bulletin, v. 95, no. 12, p. 2031–2059, doi:10.1306/03281110162.

Baumgardner, R. W., Jr., H. S. Hamlin, and H. D. Rowe, 2016, Lithofacies of the Wolfcamp and Lower Leonard intervals, southern Midland Basin, Texas: Austin, Texas, The University of Texas at Austin Bureau of Economic Geology Report of Investigations 281, 66 p.

Bernhard, J. M., 1993, Experimental and field evidence of Antarctic foraminiferal tolerance to anoxia and hydrogen sulfide: Marine Micropaleontology, v. 20, no. 3–4, p. 203–213, doi:10.1016/0377-8398(93)90033-T.

Blakey, R. C., 2003, Carboniferous-Permian paleogeography of the assembly of Pangaea, in Wong, Th. E., ed., Proceedings of the XVth International Congress on Carboniferous and Permian Stratigraphy: Royal Dutch Academy of Arts and Sciences, Utrecht, the Netherlands, August 10–16, 2003, p. 443–456.

Bohacs, K. M., O. R. Lazar, and T. M. Demko, 2014, Parasequence types in shelfal mudstone strata—Quantitative observations of lithofacies and stacking patterns, and conceptual link to modern depositional regimes: Geology, v. 42, no. 2, p. 131–134, doi:10.1130/G35089.1.

Brown, L. F., Jr., R. F. Solis-Iriarte, and D. A. Johns, 1990, Regional depositional systems tracts, paleogeography, and sequence stratigraphy, Upper Pennsylvanian and Lower Permian strata, north- and west-central Texas: Austin, Texas, The University of Texas at Austin Bureau of Economic Geology Report of Investigations 197, 116 p.

Bunting, P. J., and J. A. Breyer, 2012, Lithology of the Barnett Shale (Mississippian), southern Fort Worth Basin, Texas, in Breyer, J. A., ed., Shale reservoirs—Giant resources for the 21st century: AAPG Memoir 97, p. 322–343.

Chok, H., C. N. Smith, M. C. Dix, S. N. Hughes, M.-L. Poulsen, J. Svendsen, and H. Friis, 2014, Prediction of sandstone reservoir quality (SSRQ) using whole-rock geochemistry, Siri Canyon, Danish North Sea: Society of Petrophysicists and Well-Log Analysts 55th Annual Logging Symposium, Abu Dhabi, United Arab Emirates, May 18–22, 2014, SPWLA-2014-JJJ, 19 p.

Denne, R. A., R. E. Hinote, J. A. Breyer, T. H. Kosanke, J. A. Lees, N. Engelhardt-Moore, J. M. Spaw, and N. Tur, 2014, The Cenomanian–Turonian Eagle Ford Group of South Texas: Insights on timing and paleogeographic conditions from geochemistry and micropaleontologic analyses: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 413, p. 2–28, doi:10.1016/j.palaeo.2014.05.029.

Ellis, C. H., 1963, Micropaleontology of the Mowry Shale, New Castle Formation, and equivalent stratigraphic units, in Bolyard, D. W., and P. J. Katich, eds., Guidebook to the geology of the northern Denver Basin and adjacent uplifts: 14th field conference, Colorado, Wyoming, Nebraska, and South Dakota: Denver, Colorado, Rocky Mountain Association of Geologists, p. 149–155.

Fairbanks, M. D., S. C. Ruppel, and H. Rowe, 2016, High-resolution stratigraphy and facies architecture of the Upper Cretaceous (Cenomanian–Turonian) Eagle Ford Group, Central Texas: AAPG Bulletin, v. 100, no. 3, p. 379–403, doi:10.1306/12071514187.

Fishman, N. S., S. O. Egenhoff, A. R. Boehlke, and H. A. Lowers, 2015, Petrology and diagenetic history of the upper shale member of the Late Devonian–Early Mississippian Bakken Formation, Williston Basin, North Dakota, in Larsen, D., S. O. Egenhoff, and N. S. Fishman, eds., Paying attention to mudrocks: Priceless!: Boulder, Colorado, Geological Society of America Special Paper 515, p. 125–151.

Fishman, N. S., G. S. Ellis, A. R. Boehlke, S. T. Paxton, and S. O. Egenhoff, 2013, Gas storage in the Upper Devonian–Lower Mississippian Woodford Shale, Arbuckle Mountains, Oklahoma: How much of a role do chert beds play? in Chatellier, J.-Y., and D. M. Jarvie, eds., Critical assessment of shale resource plays: AAPG Memoir 103, p. 81–107.

Folk, R. L., 1980, Petrology of sedimentary rocks: Austin, Texas, Hemphill Publishing, 182p.

Gale, J. F. W., S. E. Laubach, J. E. Olson, P. Eichhubl, and A. Fall, 2014, Natural fractures in shale: A review and new observations: AAPG Bulletin, v. 98, no. 11, p. 2165–2216, doi:10.1306/08121413151.

Guidry, K., D. Luffel, and J. B. Curtis, 1996, Development of laboratory and petrophysical techniques for evaluating shale reservoirs: Final technical report, October 1986–September 1993: Chicago, Illinois, Gas Research Institute, 304 p.

Hackley, P. C., and B. J. Cardott, 2016, Application of organic petrography in North American shale petroleum systems: A review: International Journal of Coal Geology, v. 163, p. 8–51, doi:10.1016/j.coal.2016.06.010.

Hamlin, H. S., Jr., and R. W. Baumgardner, 2012, Wolfberry (Wolfcampian–Leonardian) deep-water depositional systems in the Midland Basin: Stratigraphy, lithofacies, reservoirs, and source rocks: Austin, Texas, The University of Texas at Austin Bureau of Economic Geology Report of Investigations 277, 61 p.

Houben, M. E., G. Desbois, and J. L. Urai, 2014, A comparative study of representative 2D microstructures in Shaly and Sandy facies of Opalinus Clay (Mont Terri, Switzerland) inferred form BIB-SEM and MIP methods: Marine and Petroleum Geology, v. 49, p. 143–161, doi:10.1016/j.marpetgeo.2013.10.009.

Isaacs, C. M., 1981, Porosity reduction during diagenesis of the Monterey Formation, Santa Barbara coastal area, California, in Garrison, R. E., and R. G. Douglas, eds., The Monterey Formation and related siliceous rocks of California: Tulsa, Oklahoma, SEPM Special Publication 15, p. 257–271.

Jarvie, D. M., 2012, Shale resource systems for oil and gas: Part 2—Shale-oil resource systems, in Breyer, J. A., ed., Shale reservoirs—Giant resources for the 21st century: AAPG Memoir 97, p. 89–119.

Jarvie, D. M., R. J. Hill, T. E. Ruble, and R. M. Pollastro, 2007, Unconventional shale-gas systems: The Mississippian Barnett Shale of north-central Texas as one model for thermogenic shale-gas assessment: AAPG Bulletin, v. 91, no. 4, p. 475–499, doi:10.1306/12190606068.

Kelly, S., H. El-Sobky, C. Torres-Verdín, and M. T. Balhoff, 2016, Assessing the utility of FIB-SEM images for shale digital rock physics: Advances in Water Resources, v. 95, p. 302–316, doi:10.1016/j.advwatres.2015.06.010.

Klemme, H. D., and G. F. Ulmishek, 1991, Effective petroleum source rocks of the world: Stratigraphic distribution and controlling depositional factors: AAPG Bulletin, v. 75, no. 12, p. 1809–1851.

Lazar, O. R., K. M. Bohacs, J. H. S. Macquaker, J. Schieber, and T. M. Demko, 2015, Capturing key attributes of fine-grained sedimentary rocks in outcrops, cores, and thin sections: Nomenclature and description guidelines: Journal of Sedimentary Research, v. 85, no. 3, p. 230–246, doi:10.2110/jsr.2015.11.

Loucks, R. G., and R. M. Reed, 2014, Scanning-electron-microscope petrographic evidence for distinguishing organic-matter pores associated with depositional organic matter versus migrated organic matter in mudrocks: GCAGS Journal, v. 3, p. 51–60.

Loucks, R. G., and S. C. Ruppel, 2007, Mississippian Barnett Shale: Lithofacies and depositional setting of a deep-water shale-gas succession in the Fort Worth Basin, Texas: AAPG Bulletin, v. 91, no. 4, p. 579–601, doi:10.1306/11020606059.

Macquaker, J. H. S., and A. E. Adams, 2003, Maximizing information from fine-grained sedimentary rocks: An inclusive nomenclature for mudstones: Journal of Sedimentary Research, v. 73, no. 5, p. 735–744, doi:10.1306/012203730735.

MacQuaker, J. H. S., and R. L. Gawthorpe, 1993, Mudstone lithofacies in the Kimmeridge Clay Formation, Wessex Basin, southern England; Implications for the origin and controls of the distribution of mudstones: Journal of Sedimentary Research, v. 63, p. 1129–1143.

Macquaker, J. H. S., and J. K. Howell, 1999, Small-scale (<5.0 m) vertical heterogeneity in mudstones: Implications for high-resolution stratigraphy in siliciclastic mudstone successions: Journal of the Geological Society, v. 156, no. 1, p. 105–112, doi:10.1144/gsjgs.156.1.0105.

Macquaker, J. H. S., M. A. Keller, and S. J. Davies, 2010, Algal blooms and “marine snow”: Mechanisms that enhance preservation of organic carbon in ancient fine-grained sediments: Journal of Sedimentary Research, v. 80, no. 11, p. 934–942, doi:10.2110/jsr.2010.085.

Milliken, K., 2014, A compositional classification for grain assemblages in fine-grained sediments and sedimentary rocks: Journal of Sedimentary Research, v. 84, no. 12, p. 1185–1199, doi:10.2110/jsr.2014.92.

Milliken, K. L., and R. J. Day-Stirrat, 2013, Cementation in mudrocks: Brief review with examples from cratonic basin mudrocks, in Chatellier, J.-Y., and D. Jarvie, eds., Critical assessment of shale resource plays: AAPG Memoir 103, p. 133–150.

Milliken, K. L., S. M. Ergene, and A. Ozkan, 2016, Quartz types, authigenic and detrital, in the Upper Cretaceous Eagle Ford Formation, south Texas, USA: Sedimentary Geology, v. 339, p. 273–288, doi:10.1016/j.sedgeo.2016.03.012.

Milliken, K. L., W. L. Esch, R. M. Reed, and T. Zhang, 2012a, Grain assemblages and strong diagenetic overprinting in siliceous mudrocks, Barnett Shale (Mississippian), Fort Worth Basin, Texas: AAPG Bulletin, v. 96, no. 8, p. 1553–1578, doi:10.1306/12011111129.

Milliken, K. L., D. K. McCarty, and A. Derkowski, 2018, Grain assemblages and diagenesis in the tarl-dominated Lower Silurian mudrock succession of the western margin of the east European craton in Poland and Lithuania: Sedimentary Geology, v. 374, p. 115–133, doi:10.1016/j.sedgeo.2018.07.011.

Milliken, K. L., and T. Olson, 2017, Silica diagenesis, porosity evolution, and mechanical behavior in siliceous mudstones, Mowry Shale (Cretaceous), Rocky Mountains, U.S.A.: Journal of Sedimentary Research, v. 87, no. 4, p. 366–387, doi:10.2110/jsr.2017.24.

Milliken, K. L., Y. Shen, L. T. Ko, and Q. Liang, 2017, Grain composition and diagenesis of organic-rich lacustrine tarls, Triassic Yanchang Formation, Ordos Basin, China: Interpretation, v. 5, no. 2, p. SF189–SF210, doi:10.1190/INT-2016-0092.1.

Passey, Q. R., K. Bohacs, W. L. Esch, R. Kimentidis, and S. Sinha, 2010, From oil-prone source rock to gas-producing shale reservoir - Geologic and petrophysical characterization in unconventional shale gas reservoirs: International Oil and Gas Conference and Exhibition in China, Beijing, China, June 8–10, 2010, SPE-131350-MS, 29 p.

Reed, R. M., and R. S. Roush, 2016, Pore systems of the Cline shale, Midland Basin, west Texas, Society of Petroleum Engineers/AAPG/Society of Exploration Geophysicists Unconventional Resources Technology Conference, San Antonio, Texas, August 1–3, 2016, URTEC-2423781-MS, 9 p., doi:10.15530/urtec-2016-2423781.

Roduit, N., 2008, JMicroVision: Image analysis toolbox for measuring and quantifying components of high-definition images (v.1.2.7), accessed November 15, 2006, https://jmicrovision.github.io.

Roush, R. S., 2015, Regional stratigraphic and core-based characterization of the Cline shale, Midland Basin, Texas, Master’s thesis, The University of Texas at Austin, Austin, Texas, 170 p.

Rowe, H., N. Hughes, and K. Robinson, 2012, The quantification and application of handheld energy-dispersive x-ray fluorescence (ED-XRF) in mudrock chemostratigraphy and geochemistry: Chemical Geology, v. 324–325, p. 122–131, doi:10.1016/j.chemgeo.2011.12.023.

Schneider, J., P. B. Flemings, R. J. Day-Stirrat, and J. T. Germaine, 2011, Insights into pore-scale controls on mudstone permeability through resedimentation experiments: Geology, v. 39, no. 11, p. 1011–1014, doi:10.1130/G32475.1.

Scholle, P. A., and D. S. Ulmer-Scholle, 2003, A color guide to the petrography of carbonate rocks: Grains, textures, porosity, diagenesis: AAPG Memoir 77, 474 p., doi:10.1306/M77973.

Sen Gupta, B. K., and M. L. Machain-Castillo, 1993, Benthic foraminifera in oxygen-poor habitats: Marine Micropaleontology, v. 20, no. 3–4, p. 183–201, doi:10.1016/0377-8398(93)90032-S.

Storvoll, V., K. Bjørlykke, and N. H. Mondol, 2005, Velocity-depth trends in Mesozoic and Cenozoic sediments from the Norwegian Shelf: AAPG Bulletin, v. 89, no. 3, p. 359–381, doi:10.1306/10150404033.

Thyberg, B., J. Jahren, T. Winje, K. Bjørlykke, J. I. Faleide, and Ø. Marcussen, 2010, Quartz cementation in Late Cretaceous mudstones, northern North Sea: Changes in rock properties due to dissolution of smectite and precipitation of micro-quartz crystals: Marine and Petroleum Geology, v. 27, no. 8, p. 1752–1764, doi:10.1016/j.marpetgeo.2009.07.005.

Tonner, D., S. Hughes, and M. Dix, 2012, Wellsite geochemistry - New analytical tools used to evaluate unconventional reservoirs to assist in well construction and smart completions: Society of Petrophysicists and Well-Log Analysts 53rd Annual Logging Symposium, Cartagena, Colombia, June 16–20, 2012, SPWLA-2012-110, 11 p.

Tribovillard, N., T. J. Algeo, T. Lyons, and A. Riboulleau, 2006, Trace metals as paleoredox and paleoproductivity proxies: An update: Chemical Geology, v. 232, no. 1–2, p. 12–32, doi:10.1016/j.chemgeo.2006.02.012.

Velde, B., 1996, Compaction trends of clay-rich deep sea sediments: Marine Geology, v. 133, no. 3–4, p. 193–201, doi:10.1016/0025-3227(96)00020-5.

Wang, C., Q. Wang, G. Chen, L. He, Y. Xu, L. Chen, and D. Chen, 2017, Petrographic and geochemical characteristics of the lacustrine black shales from the Upper Triassic Yanchang Formation of the Ordos Basin, China: Implications for the organic matter accumulation: Marine and Petroleum Geology, v. 86, p. 52–65, doi:10.1016/j.marpetgeo.2017.05.016.

Wright, W. R., 2011, Pennsylvanian paleodepositional evolution of the greater Permian Basin, Texas and New Mexico: Depositional systems and hydrocarbon reservoir analysis: AAPG Bulletin, v. 95, no. 9, p. 1525–1555, doi:10.1306/01031110127.

Yang, K.-M., and S. L. Dorobek, 1995, The Permian Basin of west Texas and New Mexico: Flexural modeling and evidence for lithospheric heterogeneity across the Marathon Foreland, in Dorobek, S. L., and G. M. Ross, eds., Stratigraphic evolution of foreland basins: Tulsa, Oklahoma, SEPM Special Publication 52, p. 149–174.

Yoon, H., and T. A. Dewers, 2013, Nanopore structures, statistically representative elementary volumes, and transport properties of chalk: Geophysical Research Letters, v. 40, no. 16, p. 4294–4298, doi:10.1002/grl.50803.

Young, H. R., and P. R. Moore, 1994, Composition and depositional environment of the siliceous Odanah Member (Campanian) of the Pierre Shale, in Manitoba, in Shurr, G. W., G. A. Ludvigson, and R. H. Hammond, eds., Perspectives on the eastern margin of the Cretaceous Western Interior Basin: Boulder, Colorado, Geological Society of America Special Papers 287, p. 175–195, doi:10.1130/SPE287-p175.

Zheng, H., 2016, Sedimentology and reservoir characterization of the Upper Pennsylvanian Cline shale, Midland Basin, Texas, Master’s thesis, The University of Texas at Austin, Austin, Texas, 141 p.

Zou, C. N., Z. Yang, S. Z. Tao, X. J. Yuan, R. K. Zhu, L. H. Hou, and S. T. Wu, et al., 2013, Continuous hydrocarbon accumulation over a large area as a distinguishing characteristic of unconventional petroleum: The Ordos Basin, north-central China: Earth-Science Reviews, v. 126, p. 358–369, doi:10.1016/j.earscirev.2013.08.006.

ACKNOWLEDGMENTS

This study was financially supported by the State of Texas Advanced Resource Recovery program at BEG and the China Scholarship Council (Grant No. 201606440062). Junwen Peng also received minor financial support from the Geological Society of America’s Graduate Student Research Grant (Grant No. 9244823). The authors thank Patrick Smith for assistance during scanning electron microscope sample preparation in the BEG imaging laboratory and Robert Reed for providing a few thin sections. Comments from Stephen Ruppel and Robert Reed improved early versions of this paper. We thank the previous AAPG Editor Barry J. Katz and three anonymous reviewers for constructive suggestions that improved the clarity of the paper. The authors would like to extend their gratitude to FireWheel Energy LLC (Houston, Texas) for their generosity in donating the core and laboratory data from the Horwood 2151-H well. The paper was edited by Bill Rader for language polishing. The technical geologic editor, Cory Godwin, from AAPG Bulletin was thanked for manuscript proofreading. Publication was authorized by the director of BEG, Jackson School of Geosciences, The University of Texas at Austin.

The Appendix is available in an electronic version on the AAPG website (www.aapg.org/datashare) as Datashare 120.

You may also be interested in ...