Quantitative Image Analysis

for Geologic Core Description

Roger J. Barnaby

DigitalStratigraphy

415 W. 15th Street

Houston, TX 77008

832-660-2945

barnabyr@outlook.com

(Key words: image analysis, quantitative core description)

mailto:barnabyr@outlook.com

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ABSTRACT 1

Many basic rock properties – such as lithology, bedding, grain size, sorting, and porosity 2

– are expressed in geologic cores by changes in color, brightness, and texture. 3

Quantitative descriptive rock properties can thus be derived from digital core images. 4

Despite the widespread availability of high-resolution core images and image analysis 5

software, these data are underutilized by geoscientists tasked with describing core. 6

This paper demonstrates the application of image analysis for quantitative core 7

description using examples from 3 different carbonate reservoirs: (1) evaporite-rich 8

dolostone from the First Eocene, Kuwait-Saudi Arabia Partitioned Zone; (2) vuggy 9

dolostone from the Cretaceous Toca Formation, offshore Angola; (3) thin-bedded 10

limestone and mudrock from the Ordovician Utica Formation, Ohio, USA. In each 11

example, quantitative data are extracted from core images using ImageJ or WellCAD 12

software. The image-derived descriptive parameters are consistent with petrophysical 13

log and core data, supporting the validity of this approach to core description. 14

Image analysis-guided core description offers many advantages over traditional hand-15

drawn core description: 1) hand-drawn core descriptions tend to be qualitative and core-16

log integration is difficult and imprecise, whereas image analysis generates quantitative 17

descriptive data that are directly comparable with petrophysical datasets; 2) image 18

analysis can characterize fine-scale geologic heterogeneity that is difficult or impossible 19

to resolve using log and core plug data and hand-drawn core descriptions; 3) image 20

analysis allows geologists to generate preliminary descriptions prior to actual core 21

viewing, a more efficient workflow that minimizes time expended in offsite core viewing, 22

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perhaps in remote locations with limited time available; 4) integration of image-derived 23

core data with petrophysical log and core data allows rigorous evaluation of core data 24

quality − before, during, and after the process of core description. 25

Image analysis thus provides a valuable tool for geoscientists to efficiently generate 26

quantitative, petrophysically significant core descriptions. 27

INTRODUCTION 28

Digital images − white light (WL) and ultraviolet (UV) color photographs and X-ray 29

computed tomography (CT) scans − are routinely acquired from whole and slabbed 30

cores. These images contain detailed information on many basic rock properties. This 31

paper demonstrates how image analysis can extract quantitative data that allow 32

geologists to generate core descriptions that are integrated with log and core data. 33

Advances in high-performance Windows PC tablets (8-16 GB RAM, 64 bit, i7 34

processors, solid state hard drives) and WellCAD and ImageJ software provide an ideal 35

platform for geoscientists to generate integrated core descriptions. Geologic 36

descriptions are drafted using a stylus on a PC tablet, directly on top of or adjacent to 37

images and petrophysical core and log data. The initial image analysis, data integration, 38

and preliminary core description can be performed using a computer prior to core 39

viewing, optimizing the time expended at offsite core facilities, which may require 40

expensive travel to remote and/or dangerous locations. Further image analysis can be 41

performed as the core is being described. 42

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The resulting quantitative core descriptions can be directly compared with log- and core-43

based petrophysical data. Image analysis provides high-resolution information on fine-44

scale geological heterogeneity that is unavailable from standard wireline and core 45

analyses and traditional core descriptions. Image-derived quantitative core descriptions 46

are useful to evaluate core datasets for possible errors or data problems. Lastly, 47

although hand-drawn geologic core descriptions may be of interest to other geologists, 48

they have limited utility for coworkers in other disciplines, such as petrophysicists, 49

reservoir modelers, and petroleum engineers who require digital geologic descriptions 50

and interpretations. 51

To illustrate the application of image analysis to geologic core description, this paper 52

describes 3 examples from heterogeneous carbonate reservoirs that are difficult to 53

quantitatively characterize using log and core data and traditional hand-drawn geologic 54

descriptions. The first example is from the First Eocene Formation in Wafra Field, 55

Kuwait-Saudi Arabia Partitioned Zone. The objective of this study was to quantify 56

possible changes to the mineralogy, reservoir quality, and fluid saturation due to 57

steamflooding. The second example, utilizing vuggy Toca dolostones from offshore 58

Angola, demonstrates how image analysis of CT scans can characterize vuggy pore 59

systems. The third example, from the Utica Formation, Ohio, USA, demonstrates how 60

image analysis can efficiently characterize laminated to thin-bedded unconventional 61

mudrock reservoirs. 62

METHODOLOGY 63

For the Wafra and Toca studies, wireline logs − gamma ray (GR), resistivity (RES), 64

neutron porosity (NPHI), density (RHOB), photoelectric absorption (PEF), caliper (CAL), 65

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and borehole image (FMI) were available; in addition to core gamma ray and core plug 66

analyses (porosity, permeability, grain density, and saturation). Log-derived mineralogy, 67

porosity, and water saturation were calculated from these data. For the Utica study, the 68

only petrophysical data utilized were core gamma ray. 69

Because log depth differs from core depth, core-log integration requires depth shifting to 70

ensure that all comparable data are at the same depth. WellCAD software was used for 71

loading, depth shifting, and integration of all log, core, and image data. The wireline logs 72

were first loaded into the document. The FMI logs were then loaded and depth shifted to 73

match the wireline logs. Next, the core gamma and core plug porosity data were loaded 74

and depth shifted to match the wireline GR log and log-derived porosity. Lastly, images 75

from the CT scans and core photographs were loaded and further depth shifted as 76

required to match the FMI log. This integrated dataset allows quantitative comparison of 77

images, logs, core data, and geologic descriptions. 78

Color WL photographs of slabbed core were available for every study. The core 79

photographs are 32 bit (Red, Green, Blue) RGB images at 72 pixels/inch (3 pixels/mm). 80

For the Wafra and Toca studies, full diameter core CT scans, acquired at a resolution of 81

300 scans/ft. (1 scan/mm), were available. These scans are 8 bit grayscale images, 82

also at 72 pixels/inch (3 pixels/mm). This study used the outside circumference of the 83

CT image for analysis, because it could be directly compared with the borehole image 84

for depth shifting. 85

Photo editing software was used to crop images from the core box photographs and 86

then mosaic the photographs into a continuous image. The CT scans, generally in 3 ft. 87

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(0.9m) lengths, were also compiled into a continuous image. The continuous images 88

from core photographs and CT scans were then sliced into uniform 1 ft. (0.3 m) lengths 89

in order to generate digital log curves of the image analysis with a 1 ft. (0.3 m) vertical 90

resolution, similar to the log and core plug datasets. Because 72 pixel/inch (3 91

pixels/mm) core photographs and CT scans were used for the analysis, small-scale 92

features < 9 pixels2 in area (e.g. < 0.002 inch2, < 1.0 mm2) were filtered out from the 93

analytical results. The images provided adequate resolution for the macro-scale 94

features of interest. 95

Quantitative image analysis of core photographs and CT scans for the First Eocene and 96

Toca studies was performed using ImageJ − a freeware, public domain program that 97

was initially developed at the National Institute of Health (NIH). ImageJ has an open 98

software architecture; its power is derived from user-written plugins and macros that are 99

customized to solve specific image processing and analysis applications. This study 100

utilized both publicly available freeware and a Chevron proprietary version of ImageJ for 101

image processing and analysis. A Macintosh spinoff version of the NIH software, Image 102

SXM, has similar customized features to those utilized by this study from Chevron 103

proprietary software. Image SXM is available for free distribution and documented in 104

detail by Heilbronner and Barrett (2014). 105

In CT scans, the density contrast between evaporite minerals, open vugs, and the host 106

dolostone can be distinguished due to the attenuation of X-rays that pass through the 107

material and are then filtered to create a monochromatic image. Anhydrite attenuates 108

the X-ray beam and displays corresponding low grayscale (white to light gray) values on 109

CT scans. Conversely, open vugs do not impede the X-rays and display high grayscale 110

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values (dark gray to black). Dolostone exhibits mid-range grayscale values (medium 111

gray). CT scan images from the Wafra and Toca studies were segmented according to 112

grayscale values using ImageJ software. The area for each phase was then computed 113

for each 1 ft. vertical slice to quantify the mineralogy and vuggy porosity. The results are 114

presented as a log curve with a data point for every foot. 115

White light photographs of core slabs were similarly analyzed using ImageJ software. 116

The images were first processed and corrected for exposure. For the Wafra study, the 117

color contrast between white anhydrite nodules and gray-colored gypsum overgrowths 118

was used to define Hue, Saturation, Brightness (HSB) parameters to distinguish 119

anhydrite from gypsum. ImageJ software was used to segment the images according to 120

the HSB parameters. The area of each mineral phase was then computed for each 1 ft. 121

vertical slice. The results are presented as a log curve with a data point for every foot. 122

Because oil stain rapidly fades after core is slabbed, WL (and UV) photographs of 123

freshly slabbed core provide better information on oil stain than actual core viewing, 124

which may be months after the core was slabbed. In the Wafra cores, oil stain is the 125

only dark-colored component, thus it can be readily quantified on the basis of color. 126

Color, as defined by HSB, was used to segment the images, using ImageJ software, 127

which then computed the area of oil stain for each 1 ft. (0.3 m) vertical slice. The results 128

are presented as a log curve with data at a 1 foot vertical spacing. 129

The Utica Formation consists of light colored, laminated to thin bedded limestones 130

interbedded with dark mudrock. In this example, core photographs were loaded into 131

WellCAD software, where the image analysis application was used to extract a single 132

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log curve representing median grayscale values at a specified vertical interval of 0.01 ft. 133

(3 mm). High grayscale values represent limestone and low values represent mudrock. 134

This dense vertical sampling captured laminated and thin-bedded vertical heterogeneity 135

that is difficult to assess with traditional hand-drawn core descriptions, wireline logs, and 136

standard diameter core plugs. 137

QUANTITATIVE IMAGE ANALYSIS 138

First Eocene Formation, Kuwait-Saudi Arabia 139

Description 140

The First Eocene is the shallowest reservoir in Wafra Field (Fig. 1). Reservoir geology 141

and production are described by Saller et al. (2014) and Meddaugh et al. (2007; 2011a; 142

2011b). The reservoir (Fig. 2) consists of cyclic peritidal dolostones with intercrystalline 143

porosity. Porosity and permeability values range up to 50% and 6000 mD. Evaporites 144

are present as dispersed and coalesced nodules and up to 5-ft-thick (1.5 m) bedded 145

units. Anhydrite is the dominant evaporite mineral, gypsum occurs as a thin (0.4 inch, 1 146

cm thick) outer rind on evaporite nodules. 147

Because of poor primary oil recovery (Champenoy et al. 2011; Rubin 2011), 148

steamflooding in the First Eocene Wafra reservoir began in 2006 (Barge 2009; 149

Meddaugh 2011b). Steam was injected into a 50 ft. (15 m) thick zone where porous 150

dolostones are overlain by tight, finely crystalline dolostone and bedded evaporite, 151

which provide a vertical barrier to steamflood (Fig. 2). The previously cored "Well A" 152

was used to monitor the thermal buildup (Figs. 3 and 4) associated with steam injection 153

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(Meddaugh et al. 2011a; 2011b). In the first 3 years, the temperature in the 154

steamflooded zone increased by nearly 200oC. To monitor the effects of steamflood on 155

the reservoir fluid and rock properties, "Well B" was drilled in 2012, at a lateral distance 156

of 70 ft. (21 m) away from the previously cored "Well A" (Fig. 3). Core was acquired in 157

order to petrographically and petrophysically compare the pre- and post-steamflood 158

cores, with the intent of quantifying possible steamflood-induced changes in mineralogy, 159

reservoir quality, and fluid saturation and to evaluate the steamflood sweep efficiency. 160

Comparison of the two closely-spaced cores indicates that the depositional facies, rock 161

fabric, and diagenetic features are nearly identical. In the interval above the steamflood 162

zone, the two cores display similar properties with respect to oil stain, saturation, 163

mineralogy, and porosity. Within the steamflood zone, however, the post-steamflood 164

core exhibits a significant decrease in oil stain compared to the correlative interval in the 165

pre-steamflood core (Fig. 5). Evaporite nodules in the pre-steamflood core consist of 166

white masses of anhydrite with a medium gray outer rind, up to 0.4 inch (1 cm) thick, 167

composed of gypsum. In the steamflooded core, evaporite nodules exhibit a tan oil stain 168

and gypsum is absent. 169

Results 170

CT scan images were segmented according to grayscale to delineate total evaporite 171

content (Fig. 6). The amount of visual evaporite was calculated using ImageJ and 172

presented as a log curve (Fig. 7). The image-derived mineral volumes are consistent 173

with the log-derived mineralogy based on multimin analysis. 174

Because anhydrite is white and gypsum is medium gray, the two minerals can be 175

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distinguished in core photographs (Figs. 8 and 9). The two minerals also are identified 176

in thin sections using standard petrographic techniques (Figs. 8 - 10). ImageJ was used 177

to segment the core photographs to delineate anhydrite and gypsum (Fig. 11).The 178

amount of each mineral phase was computed at 1 foot (0.3 m) intervals, generating a 179

quantitative curve for the amount of gypsum and anhydrite (Fig. 12). The image-derived 180

mineral volumes are consistent with log-derived mineralogy using multimin analysis. 181

Image analysis indicates that the pre-steamflood core from Well A locally contains up to 182

28% gypsum, with an average value of 12% over the steamflood-equivalent zone, 183

whereas little to no gypsum occurs over this interval in the post-steamflood core from 184

Well B (Fig. 13). Thin section petrography (Fig. 10) provides direct evidence of gypsum 185

dissolution. Intervals that exhibit gypsum dissolution display a corresponding increase in 186

porosity (Fig. 13). Core plugs and logs indicate that porosity increased as much as 10-187

15% locally, with an average of 2-3% porosity increase. 188

Comparison of the log-derived porosities for the pre- and post-steamflood wells 189

confirms an increase in porosity due to gypsum dissolution (Fig. 14). In post-steamflood 190

Well B, the porosities are skewed to higher average and median values than the 191

porosity values from the pre-steamflood well. A cross plot of the log-derived total 192

porosity (PHIT) curves for the steamflooded zones confirms the interpretation that 193

selective dissolution of gypsum created porosity (Fig. 15). The two wells exhibit similar 194

porosities where only minor gypsum ( 7.5%), the porosity values in the post-steamflood well are up 196

to 10-15% greater than in the pre-steamflood well. 197

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The amount of oil stain was computed from the core photographs using ImageJ. 198

Comparison of the core photographs and the segmented images (Fig. 16) demonstrates 199

how core plug saturations will differ from image analysis due to small scale 200

heterogeneity. Although both techniques yield quantitative results, they are based on 201

entirely different sample volumes; 1.5 inch (3.7 cm) core plugs vs. 1 ft. (0.3 m) core 202

photographs. In general, the results from the two techniques are consistent (Fig. 17). 203

Within the steamflooded reservoir, quantitative image analysis documents locally up to 204

95% reduction in oil stain, with an average of 66% oil stain reduction (Fig. 17). Core 205

plug oil saturation data are consistent with these calculations. Core plugs from the 206

steamflood zone indicate locally up to 95% recovery, with an average of 76% recovery 207

over the interval, while log analyses indicate a slightly lower average of 57% oil 208

recovery (Fig. 17). Image analysis of oil stain from core photographs can thus yield 209

results comparable with log and core data. 210

Discussion 211

Image analysis of core photographs indicates extensive gypsum dissolution in Wafra 212

Field due to steamflood, which caused a corresponding increase in porosity. 213

Quantitative image-derived estimates of the amount of gypsum dissolution are 214

supported by petrophysical core and log data. These interpretations imply significant 215

mobilization of gypsum during steamflood, which is supported by reports of CaSO4 216

scale buildup causing production problems. Thin section petrography and image 217

analysis indicate that gypsum dissolution is confined to the outer periphery of evaporite 218

nodules, which could impact enhanced oil recovery by channeling steamflood and 219

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reducing matrix sweep. This demonstrates that image analysis has valuable high-220

resolution reservoir description capabilities that are unmatched by other techniques. 221

Quantitative analysis of core photographs indicate that steamflood caused, on average, 222

a 66% reduction in oil stain (Fig 17). This is consistent with log- and core-derived 223

estimates of oil recovery ranging from 57% to 76%, respectively. Moreover, image 224

analysis yields a high-resolution, better than 0.05 inch (1 mm), characterization of the 225

heterogeneous distribution of residual oil (Fig 16) than is possible using logs and 226

standard diameter core plugs. This high-resolution characterization of oil recovery is 227

critical for evaluating the effectiveness of matrix sweep by steamflood. It also provides a 228

framework for further investigations of fine-scale geological heterogeneity using high 229

resolution CT plug scans, micro-permeameter analysis, and detailed petrography. 230

Cretaceous Toca Dolostones: Offshore Angola 231

Because vuggy pore systems can create permeabilities that are orders of magnitude 232

greater than matrix porosity (Lucia 1999), vugs strongly influence reservoir 233

performance. Vuggy reservoirs are challenging to accurately describe using wireline 234

logs, core plugs, and hand-drawn geologic core descriptions. While the neutron porosity 235

(NPHI) and density (RHOB) logs will quantify the total volume of porosity, these logs 236

cannot distinguish between matrix and vuggy porosity. Core plugs tend to 237

underestimate vuggy porosity due to sampling bias, because of the difficulty in cutting 238

intact plug samples from vuggy rocks. Traditional hand-drawn geologic core 239

descriptions must rely upon qualitative terms (e.g., rare, common, abundant) to describe 240

the amount of vuggy porosity, 241

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An example from the Toca Formation, offshore Angola, serves to illustrate the 242

application of image analysis in characterizing vuggy pore systems, Toca reservoirs 243

consist of vuggy dolomitized skeletal grainstones and packstones. Abundant vugs, up to 244

10 cm in diameter, are evident in CT scans, core photographs, thin sections, and 245

borehole images (Figs. 18-20). 246

CT scans were used to quantify the vuggy porosity (Fig. 19). Core photographs and thin 247

section scans could also be used to quantify vugs. These methods, however, 248

investigate a smaller volume of rock than the full diameter core CT scans. The CT 249

scans were examined to eliminate coring-induced breakage and fractures from the 250

analysis. Using ImageJ software, the area of the vugs was calculated (Fig. 19). The 251

computed vug, presented as a log curve (Fig. 20), is consistent with the log-derived total 252

porosity (PHIT), indicating that the porosity in this interval is dominated by vugs rather 253

than by matrix porosity. Core plug porosity measurements generally underestimate 254

vuggy porosity (Fig. 20) due to sampling bias, because it is impossible to acquire intact 255

core plugs from intervals with large vugs. Quantitative image analysis thus provides the 256

best technique to accurately characterize vuggy pore systems from core. 257

Thin-Bedded Unconventional Reservoir: Utica Formation, USA 258

Laminated to thin-bedded mudrocks pose a challenge to petrophysical log analysis 259

because bed thickness is below the resolution of most wireline logs. Moreover, it is 260

difficult to obtain representative standard diameter core plug samples from thin beds 261

and laminae. Detailed characterization of the intercalated lithologic units using 262

traditional hand-drawn core description techniques is labor-intensive and prone to error. 263

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Small errors in the measured depth will place the beds and bed boundaries at the 264

incorrect depth. Moreover, it is challenging to consistently describe every thin bed and 265

lamination, especially in a long core that requires days of effort to describe. 266

Because of the color contrast in alternating thin beds and laminae in most mudrock 267

successions, image analysis is an excellent application to characterize these reservoirs. 268

An example from the Utica Formation, in Ohio, USA, exhibits the fine-scale layered 269

heterogeneity typical of these interbedded light gray skeletal limestones and dark gray, 270

organic-rich mudrocks (Fig. 21). In this case, the WellCAD image module was used to 271

extract a log curve of median grayscale values sampled at 0.01 ft. (3 mm) intervals. 272

The computed grayscale curve (Fig. 21), is similar to a grain-size profile drawn by a 273

geologist during traditional, hand-drawn core description. The grayscale curve 274

represents interbedded units of clean limestone and mudrock. The computer-generated 275

profile is more precise than a hand-drawn description and eliminates hours (or days) of 276

meticulous observation and description. The initial computer-generated curve can be 277

manually edited as required during the core viewing. 278

QUANTITATIVE CORE DESCRIPTION: ANALYSIS OF CORE DATA QUALITY 279

An important advantage of quantitative core description is that it facilitates a review of 280

the core data quality. Errors in core datasets are quite common. For example, core 281

depths can be mislabeled, lengths of core may be flipped or misplaced, cores are 282

sometimes dropped and pieced back together by inexperienced staff, and sample points 283

can be incorrectly recorded. Sometimes errors are created before the full diameter 284

cores are CT scanned, sampled, analyzed, and photographed. Errors also are 285

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introduced when cores are slabbed, boxed, labelled, and photographed. Core 286

mishandling by geoscientists, unfortunately, is another source of error for subsequent 287

core descriptions. 288

With traditional hand-drawn core descriptions, errors in the core database may be 289

difficult to recognize. Often, geologists describe core straight from the core boxes, 290

implicitly assuming that the core was properly handled and the core boxes were 291

correctly labeled. Because hand-drawn core descriptions tend to be qualitative and 292

core-log integration is imprecise, errors in the core database may not be identified 293

during the core description. I have seen many core descriptions that failed to recognize 294

that pieces or sections of the core were out of place or that sample analyses were 295

reported at the wrong depths. 296

Quantitative core description requires precise depth matching of log and core datasets. 297

By depth-shifted core images and core data to match the wireline logs and borehole 298

images, errors and mismatches become evident. Using this workflow, I have identified 299

errors in approximately half of the cores that I have examined. Fortunately, such errors 300

can be readily identified and rectified. Two examples serve to illustrate problems 301

common in core datasets. 302

The first example is the post-steamflood core, Well B, from Wafra Field. When core 303

images from the CT scans and slabbed photographs were depth-shifted to match the 304

logs, log analysis, and borehole images, it became evident that the core-log data could 305

not be reconciled at the depth interval of 1073-1079 ft. (Fig. 22). Examination of the 306

core slabs and butts indicates that two core pieces, 1073-1075.6 ft. and 1076-1078.6 ft., 307

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were accidentally switched and mislabeled, with the additional complication that a 0.4 ft. 308

pieces at the bottom of each length were correctly labeled (Fig. 23). This error occurred 309

prior to CT scanning, core gamma ray analysis, and plug sampling of the full diameter 310

core. The error persisted after the core was slabbed and photographed. Consequently, 311

the entire core dataset over this 6 ft. interval – CT scans, core photographs, core 312

gamma ray, and core plug analyses – had incorrect reported depths. These errors were 313

not detected by geologists who previously described this core. By rearranging the core 314

pieces to the correct positions (Fig. 23) and editing the image and core analysis data to 315

the proper depths, we can see that there now is an excellent match between the core 316

and log data (Fig. 24). 317

The second example of errors in a core dataset is from the Utica Formation. As 318

described above, the grayscale curve computed from the core photographs (Fig. 21) 319

represents interbedded units of light gray limestone and dark gray mudrock. Because 320

clean limestones have low gamma ray values and dark mudrocks have high gamma ray 321

values, the grayscale curve should be comparable to the core gamma ray log. 322

The core gamma data, as reported, are shown as the red log curve (Fig. 25). This curve 323

appears to be out of phase with the core image − dark gray mudrocks that have high 324

gamma ray signatures appear to correspond to lower values in the core gamma ray log 325

and limestones that have low gamma ray signatures appear to correspond to higher 326

values in the core gamma ray. This apparent mismatch between the core photos and 327

core gamma arises from core gamma ray acquisition procedures. The scintillometer tool 328

begins measurement of gamma ray emissions at the bottom of the core and records 329

data as the tool is slowly moved upward relative to the core. A 1 ft. (0.3 m) moving 330

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average is typically reported − beginning after the first 1 foot (0.3 m) of data are 331

recorded. For example, if the bottom of the core is 10,000 ft. (3048 m), the first reported 332

value will be at 9,999 ft. (3047.7 m) and it will represent the average value of the interval 333

between 9,999 and 10,000 ft. (3.047.7 - 3048.0 m). 334

By shifting the core gamma ray curve downward by 1 ft. (0.3 m), there is a better match 335

between the core photos and the gamma data, as shown by the green log curve (Fig. 336

25). Although this depth shift improves the overall depth match, it still will not be perfect 337

because of the core gamma ray averaging techniques. In thin-bedded reservoirs, the 338

most accurate technique to depth match core to log data is to tie the core images (CT 339

scans, photographs) to borehole images. 340

This mismatch between core depth and the core gamma ray log, as reported, is 341

generally not recognized during the process of traditional hand-drawn core description 342

and petrophysical analysis. Traditionally, the core gamma ray log provides the standard 343

for depth shifting core data to match wireline logs. However, as this example shows, this 344

practice will result in a mismatch between the core and log data. Core plug data will be 345

offset from the wireline logs by 1 ft., a significant error in these laminated to thin-bedded 346

mudrock reservoirs. 347

SUMMARY AND CONCLUSIONS 348

Quantitative geological descriptions can be readily derived from routine core images 349

using free, open-source software (ImageJ) and widely used commercial software 350

(WellCAD). This technology enables geologists to generate digital core descriptions that 351

are fully integrated with wireline logs, images from borehole and core, and core 352

17

analyses. Image analysis efficiently captures fine-scale geologic heterogeneity that is 353

difficult to resolve using standard log and core plug data and traditional hand-drawn 354

core descriptions. Image analysis and petrophysical integration is performed using a 355

computer to generate a preliminary description prior to the actual core viewing. This 356

optimizes the time expended describing core at offsite core viewing facilities, which may 357

require travel to remote locations with limited time available. Lastly, quantitative core 358

description facilitates the critical evaluation of core-based data for possible errors. 359

This paper describes 3 examples of image analysis-generated core descriptions from 360

carbonate rocks. Whole core CT scans and slab core photographs from dolostones in 361

the First Eocene Formation in Wafra Field provide quantitative data on the impact of 362

steamflood to the mineralogy, porosity, and oil saturation of the reservoir. Image 363

analysis documents that steamflooding caused gypsum dissolution, consistent with log 364

and core data that indicate a paucity of gypsum in the steamflooded interval, 365

accompanied by a corresponding increase in porosity. Image analysis records an 366

average of 66% reduction in oil stain in the steamflood intervals, consistent with log and 367

core saturation analyses. Moreover, image analysis allows a high-resolution 368

understanding of steamflood-induced changes to the reservoir − beyond the resolution 369

of log and core plug data. Image analysis demonstrates that gypsum dissolution is 370

confined to the margins of the evaporite nodules and that oil sweep is highly variable 371

due to small-scale geological heterogeneity created by patchy evaporite distribution. 372

Quantitative characterization of vuggy porosity from carbonates has long eluded the 373

capabilities of traditional hand-drawn core description. Toca Formation vuggy 374

dolostones provide an example to demonstrate how image analysis can characterize 375

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vuggy pore systems. The vugs range up to 4 in (10 cm) in size, too small to be 376

individually resolved by wireline logs and too large to be characterized by standard 377

diameter core plugs. Whole core CT scans provide a means to accurately quantify the 378

contribution of vugs to the total porosity. In this example, vugs account for nearly all of 379

the porosity that is identified from the wireline logs, consistent with thin section 380

petrography. 381

Thin-bedded to laminated unconventional reservoirs such as the Utica Formation are 382

challenging to petrophysically characterize because bed and laminae thickness is below 383

the resolution of wireline logs and standard diameter core plugs. Traditional geological 384

characterization of these finely layered, heterogeneous reservoirs by hand-drawn core 385

description is laborious and unlikely to generate quantitative data. The color contrast 386

due to interbedded different lithologies, however, enables image analysis of core 387

photographs to efficiently generate quantitative geologic descriptions. 388

These examples demonstrate that image analysis is a viable technology that should be 389

more widely utilized by geologists. The time expended to learn this technology is 390

compensated by the ability to efficiently generate quantitative core descriptions. Lastly, 391

traditional hand-drawn geologic core descriptions have limited utility for coworkers in 392

other disciplines, such as petrophysicists, modelers, and reservoir engineers, who 393

require digital geologic descriptions and interpretations. 394

ACKNOWLEDGEMENTS 395

S.L. Bachtel and M.J. Seibel, Chevron Energy Technology, described depositional 396

facies and interpreted the stratigraphy for the two study cores. R. Salazar-Tio, also of 397

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Chevron Energy Technology, assisted with image processing and analysis. I thank the 398

Partitioned Zone Saudi Arabian Chevron and Chevron Energy Technology in granting 399

permission to publish this work. I thank Advanced Logic Technology for use of a 400

WellCAD license to prepare the figures. The manuscript benefited from reviews by M. 401

Minzoni, Dave Pivnik, Leslie Melim, and two unnamed JSR reviewers. 402

REFERENCES CITED 403

Barge, D., Al-Yami, F., Uphold, D., Zahedi, A., and Deemer, A., 2009, Steamflood 404

piloting the Wafra Field Eocene reservoir in the Partitioned Neutral Zone, between 405

Saudi Arabia and Kuwait, SPE 120205, 21p. 406

Champenoy, N., Rowan, D., Gonzalez, G., Aziz, S., Blackwood, S. and Meddaugh, 407

W.S., 2011, Understanding the historical assessment of reservoir performance (HARP) 408

of the First Eocene reservoir for future steam flooding, PZ, Saudi Arabia and Kuwait: 409

SPE 150578, 19p. 410

Heilbronner, R, and Barrett, S, 2014, Image Analysis in Earth Sciences: Microstructures 411

and Textures of Earth Materials, Springer-Verlag Berlin Heidelberg, 520 p. 412

Lucia, F.J. 1999, Carbonate Reservoir Characterization, Springer-Verlag, 226 p. 413

Meddaugh, W.S., Dull, D., Garber, R.A., Griest, S., Barge, D., 2007, The Wafra First 414

Eocene Reservoir, Partitioned Neutral Zone (PNZ), Saudi Arabia and Kuwait: geology, 415

stratigraphy, and static reservoir modeling: SPE 105087, 11p. 416

Meddaugh, W.S., Osterloh, W.T., Toomey, N, Bachtel, S., Champenoy, N., Rowan, D., 417

20

Gonzalez, G., Aziz, S., Hoadley, S.F., Brown, J., Al-Dhafeeri, F.M., and Deemer, A.R., 418

2011a, Impact of reservoir heterogeneity on steamflooding, Wafra First Eocene 419

Reservoir, Partitioned Zone (PZ), Saudi Arabia and Kuwait, SPE 150606, 19 p. 420

Meddaugh, W.S., Osterloh, W.T., Gupta, I., Champenoy, N., Rowen, D., Toomey, N., 421

Aziz, S., Hoadley, S., Brown, J., and Al-Yami, F., 2011b, The Wafra Field First Eocene 422

carbonate reservoir steamflood pilots: geology, heterogeneity, steam/rock interaction, 423

and reservoir response, SPE 158324, 29p. 424

Rubin, E., 2011, Full field modeling of Wafra First Eocene reservoir 56-year production 425

history, SPE 150575, 15p. 426

Saller, A.H., Pollitt, D., and Dickson, J.A.D., 2014, Diagenesis and porosity development 427

in the First Eocene reservoir at the giant Wafra Field, Partitioned Zone, Saudi Arabia 428

and Kuwait: AAPG Bull 98, p. 1185-1212. 429

430

21

FIGURE CAPTIONS 431

Figure 1. Location map for Wafra Field and generalized stratigraphic column. First 432

Eocene is the shallowest reservoir interval. Modified from Saller et al. (2014). 433

Figure 2. Stratigraphic summary from Bachtel (2014 unpublished). First Eocene 434

Formation consists of cyclic interbedded restricted platform dolomitized peritidal facies. 435

The steamflood test interval occurs within porous subtidal peloid dolopackstones in 436

upper Sequence 2 that are overlain by tight finely crystalline dolomites from mud-437

dominated intertidal facies and bedded anhydrite. 438

Figure 3. Base map for Wafra First Eocene steamflood test that initiated in 2006. The 439

design shows an inverted 5-spot pattern, with the steam injector well in the center 440

flanked by 4 producers. Well A was cored in 2004, prior to steamflood, and served as 441

an observation well to monitor temperature buildup during steam injection. Post-442

steamflood Well B was cored in 2012 at a lateral distance of 70 ft. from the previous 443

core. From Barge et al. (2009). 444

Figure 4. Temperature observation well (Well A) exhibiting reservoir heating due to 445

steam injection through time, and the stratigraphic intervals of offset injector and 446

production wells. From Barge (2010) unpublished report. 447

Figure 5. Correlative cored intervals from pre- and post-steamflood wells. Post-448

steamflood core exhibits less oil stain than pre-steamflood core due to steam-induced 449

oil sweep. Note that the evaporite nodules in the pre-steamflood core have a different 450

appearance compared with the post-steamflood core. In the pre-steamflood core, white 451

22

anhydrite evaporite nodules have an outer rind of medium gray gypsum; whereas 452

gypsum is absent in post-steamflood evaporite nodules, which exhibit a tan oil stain. 453

Figure 6. CT core scan (360o full diameter outer circumference) on left. High-density 454

evaporite nodules cores appear as white. Segmented image on right created by 455

assigning a label to each pixel based on grayscale value, pixels with grayscale values 456

between 180 and 255 identified as evaporite (anhydrite and gypsum) depicted in black 457

on right image. Total area of evaporites in this 1 ft. long core calculated at 56.87% using 458

ImageJ software. 459

Figure 7. Comparison of total evaporite derived from CT scan image versus multimin-460

derived petrophysical analysis. The results from image analysis are consistent with 461

petrophysical-based interpretation. 462

Figure 8. Evaporite nodule petrography from pre-steamflood Well A. A) core 463

photograph, evaporite nodule consists of white anhydrite, with outer rim of medium gray 464

gypsum. B) and C) paired plane light and cross polar photomicrographs. Center of 465

evaporite nodule dominated by randomly oriented lathes of anhydrite (high relief and 466

high birefringence), outer margin of nodule dominated by blocky crystals of gypsum (low 467

order gray birefringence) with scattered anhydrite inclusions. No evidence of gypsum or 468

anhydrite dissolution. Note local coarse crystals of calcite (cc) stained pink by alizarin 469

Red S along outer periphery of nodule. This calcite was interpreted by Saller et al 470

(2014) to represent biogenic SO4 reduction associated with oil degradation prior to 471

reservoir development. D) core photograph, evaporite nodule core comprised of white 472

anhydrite, with medium gray outer rim composed of gypsum. E) and F) paired plane 473

23

light and cross polar photomicrographs. Outer margin of evaporite nodule consists of 474

gypsum with scattered inclusions of anhydrite, grading into anhydrite-dominated center 475

of nodule. No evidence of gypsum or anhydrite dissolution. Calcite (cc) stained pink by 476

alizarin Red S along outer periphery of nodule. 477

Figure 9. Evaporite nodule petrography from post-steamflood Well B above 478

steamflooded zone. A) core photograph, evaporite nodule cores consist of white 479

anhydrite, with outer rim composed of medium gray gypsum. B) cross polar 480

photomicrograph. Center of evaporite nodule dominated by randomly oriented lathes of 481

anhydrite, outer margin dominated by blade-like crystals of gypsum with scattered 482

anhydrite inclusions. No evidence of gypsum or anhydrite dissolution. C) core 483

photograph, evaporite nodule core consists of white anhydrite, with outer rim of medium 484

gray gypsum. Light tan material is styrofoam used to stabilize broken core pieces. D) 485

cross polar photomicrograph. Center of evaporite nodule dominated by randomly 486

oriented lathes of anhydrite. Outer margin of nodule, adjacent to host rock, dominated 487

by blocky crystals of gypsum with scattered anhydrite inclusions. No evidence of 488

gypsum or anhydrite dissolution. 489

Figure 10. Evaporite nodule petrography from Well B steamflooded interval. A) core 490

photograph, chalky white outer rind corresponds to leached gypsum with residual 491

anhydrite, anhydrite nodule cores exhibit light tan oil stain. B) and C) plane light 492

photomicrographs. Outer periphery consists of residual anhydrite lathes, matrix gypsum 493

completely dissolved, creating porosity (filled with blue-dyed epoxy), whereas the 494

anhydrite-rich evaporite nodule core remains unaltered. D) core photograph, chalky 495

white outer rim corresponds to leached gypsum with residual anhydrite. Thin rim of 496

24

remnant gypsum indicates that gypsum dissolution initiated along the outer periphery of 497

evaporite nodules, moving towards the nodule center through time. E) and F) paired 498

plane light and cross polar photomicrographs. Magnified view of (D) showing thin rim of 499

remnant gypsum (low order gray birefringence), dividing unaltered anhydrite (high relief 500

and high birefringence) in upper portion of photograph from leached gypsum filled by 501

blue-dyed epoxy in lower photograph. 502

Figure 11. Image analysis of core photographs to calculate volume of evaporite 503

minerals. A) core photograph, each slice is 1 ft. B) segmented image, black represents 504

anhydrite, blue is gypsum, brown is background dolomite. C) calculated anhydrite 505

volume for each 1 ft. slice. D) calculated gypsum volume for each 1 ft. slice. 506

Figure 12. Comparison of visual mineralogy volumes derived from image analysis with 507

computed mineral volumes from petrophysical multimin analysis. The two different 508

techniques yield consistent results, although image analysis provides higher resolution 509

information of geologic heterogeneity. 510

Figure 13. Comparison of mineralogy and porosity between pre-steamflood Well A and 511

post-steamflood Well B. Interval that is shown is confined to steamflood zone in Well B 512

and correlative interval in Well A. PHIT is log-derived total porosity. Well A contains 513

gypsum, whereas Well B does not. The paucity of gypsum in Well B corresponds to an 514

increase in plug and log porosity, recording gypsum dissolution during steamflood. 515

Figure 14. Histogram comparison of log-derived porosity between Well A and Well B in 516

steamflood zone. Post-steamflood porosity does not exhibit as many low values as the 517

pre-steamflood values, the porosity values exhibit a more narrow range, and the 518

25

average and median values are greater. 519

Figure 15. Cross plot of log derived porosity between Well A and Well B confined to 520

steamflood zone and correlative interval. For intervals with minor gypsum (7.5%), the 522

post-steamflood Well B exhibits greater porosity. Steamflood thus causes an increase in 523

porosity in the initially tighter, gypsum-rich lithologies, whereas the more porous, 524

dolomitic lithologies are unaltered. 525

Figure 16. Core photographs and segmented images of visual oil stain. Each pixel is 526

assigned a value (oil-stained or not oil-stained), based on hue, saturation, and 527

brightness thresholds using ImageJ software. Each core piece is 1 ft. in length. Plug oil 528

saturation (So) values compared with image analysis of oil stain volume. In a highly 529

heterogeneous reservoir, core plugs do not adequately represent the larger scale 530

reservoir properties; whereas images provide a larger sample size that better matches 531

wireline log data. Moreover, image analysis provides higher resolution data of the 532

distribution of oil stain. 533

Figure 17. Comparison of Well A (pre-steamflood) and Well B (post-steamflood) cores 534

for visual oil stain, plug saturation, and log-derived saturation. From left to right 1) Well 535

A core photograph, visual oil stain segmented image, visual oil stain volume (0-100%, 536

increasing to right), and plug oil saturation (So) and water saturation (Sw); 2) Well B 537

core photograph, visual oil stain segmented image, visual oil stain volume, and plug So 538

and Sw; 3) Δ (Well A values - Well B values) between these 2 wells with respect to 539

visual oil stain, plug So, and log-derived oil saturation. Steamflooded zone in Well B 540

26

exhibits less oil stain than correlative interval in Well A, suggesting an average of 66% 541

oil recovery, consistent with core and log data indicating 76% and 57% recovery, 542

respectively. 543

Figure 18. Images of vuggy porosity in dolomitized coquina facies. CT scan on left is 544

360o full diameter outer circumference image. Other samples with smaller scale vugs 545

exhibited by core slab and thin section images (impregnated with blue dyed epoxy). 546

Figure 19. Work flow for quantitative image analysis of vuggy porosity from CT scans. 547

Open void space in CT scans has low grayscale (black) values and is readily 548

distinguished from host dolostone. Induced core breakage is identified (middle image) 549

and eliminated from analysis, showing vug porosity in red. CT scans were next sliced 550

into 1 ft. images for image analysis with example output summary from ImageJ 551

software. 552

Figure 20. PHIT (total log-derived porosity) compared with image analysis of vuggy 553

porosity (red) indicates that vugs account for nearly all of the porosity in this interval of 554

dolomitized coquina grainstones and packstones, consistent with thin section 555

petrography. 556

Figure 21. Utica Formation composed of light gray skeletal limestone interbedded with 557

dark gray mudrock. Grayscale profile, computed using WellCAD software based on core 558

photographs, generates a lithologic profile similar to geological hand-drawn core 559

descriptions. This profile can be further edited during the core viewing. 560

27

Figure 22. Depth-shifted CT scan and core photograph do not match borehole image or 561

petrophysical analysis at recorded depths 1073-1079, indicating that there are problems 562

in the core dataset. 563

Figure 23. Core box photographs shows that two pieces of core were transposed and 564

mislabeled. This error originated soon after the core was acquired, either at the wellsite 565

or when the full diameter core was first cut into 3 ft. lengths, boxed, and labeled. This 566

error compromises the entire core dataset − full diameter CT scans, core gamma ray, 567

core plug samples, core photographs, and previous geologic core descriptions. 568

Figure 24. After correcting and editing core images, there now is an excellent match 569

between depth-shifted CT scan and core photograph with borehole image and 570

petrophysical analysis. 571

Figure 25. Utica Formation computed grayscale profile (from Fig. 21). Because light 572

gray limestones have lower core gamma ray values than dark gray mudrocks, the 573

grayscale profile should correspond to the core gamma ray log. The gamma ray log, as 574

reported (red curve) displays lower values for mudrocks, for example at 6221, 6224, 575

and 6226 ft. and higher values for limestones, for example at 6219, 6223, and 6225 ft. 576

This depth mismatch is due to core gamma acquisition statistics (see text). Shifting the 577

core gamma downward by 1 ft. (green curve) exhibits a better match between image 578

and core gamma data. 579

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GR0 80GAPI

AHT300.2 2000OHMM

AHT900.2 2000OHMM

NPHI0.6 -0.1V/V

RHOB1.85 2.95G/C3

TEMPERATURE 25 DEG C 225

MAR 2006

APR 2006

MAY 2006

JULY 2006

DEC 2006

DEPTH FT

1125

1150

1175

1200

1225

1250

CORRELATIVEPRODUCTION

CORRELATIVEPRODUCTION

CORRELATIVEINJECTION

Figure 4

Pre-Steamflood Core

Post-Steamflood Core

1 ft

Evaporite Nodules

Oil-Stained Host Dolomite

Figure 5

Figure 6

EvaporiteNodules

HostDolomite

Figure 7

A B

C

D

E F

anhydrite

gypsum

cc

anhydrite

gypsum

anhydrite

gypsum

anhydrite

gypsum

cc

Figure 8

1 inch

500 µ

1 inch

500 µ

A B

anhydrite

gypsum

gypsum

anhydrite

anhydrite

gypsum

C

anhydrite gypsum

D

Figure 9

1 inch

500 µ

500 µ

1 inch

A

B

C

D

E F

anhydrite

leached gypsum

anhydrite

leached gypsum

residual gypsum

leached gypsum

anhydrite

residual gypsum

anhydrite

leached gypsum

Figure 10

1 inch 500 µ

500 µ 1 inch

1000 µ

Figure 11 % Anhydrite

Image Analysis % Gypsum

Image Analysis

1 ft

Core Photos Segmented Image

Brown=Host Dolomite Black=Anhyrite Blue=Gypsum

Segmented image – black anhydrite from Figure 12 B

Segmented image – blue gypsum from Figure 12 B

Figure 13

Gypsum = Gypsum Volume from Image Analysis

Anhydrite = Anhydrite Volume from Image Analysis

Δ Gyps = Gypsum Volume Well A ‐Gypsum Volume Well B

Δ Poros = Core Plug Porosity Well B ‐Core Plug Porosity Well A

Δ PHIT = Log‐derived Porosity Well B ‐Log‐derived Porosity Well B

Well A Well B Comparison

Visual Mineralogy

Dolomite

Gypsum

Anhydrite

Figure 14

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55

FREQ

UEN

CY

POROSITY

Well A ‐ Pre‐steamflood

Well B ‐ Post‐Steamflood

Well A Avg 0.33, median 0.35Well B Avg 0.35, median 0.37

HISTOGRAM OF LOG‐DERIVED POROSITY

Figure 15

LOG‐DERIVED POROSITY WELL A vs. WELL B

0

0.1

0.2

0.3

0.4

0.5

0.6

0 0.1 0.2 0.3 0.4 0.5 0.6

PHIT W

ell B

 (fraction)

PHIT Well A (fraction)

 7.5% Gypsum

29.6% 64.8% 32.1% 28.8%22.6% 42.1% 51.5% 31.2%

PlugOil Saturations 

Image Analysis% Oil Stain Figure 16

Figure 17

Well A Well B COMPARISON

Oil Stain = segmented image

%Oil Stain = from image analysis

Plug So = plug oil saturation

Plug Sw = plug water saturation

Delta Stain = (%Oil Stain Well A) – (%Oil Stain Well B)

Delta So = (Plug So Well A) ‐ (Plug So Well B)

Delta XOIL = (log‐based oil saturation Well A) –(log‐based saturation Well B) 

VUGGY DOLOSTONE

CT SCAN CORE SLAB

THIN SECTION

1 FT

1 INCH

1 CM

Figure 18

3 FT

QUANTITATIVE IMAGE ANALYSIS OF VUG POROSITY FROM CT SCANS

GR

0 200GAPICT Scan

Core Photo

PHIT

0.4 0V/VCT Vug Porosity

40 0Plug Por

40 0

Core DescriptionFMI

9290

9295

9300

9305

9310

9315

Figure 20

Depth Core Photo Profile6157

6158

6159

6160

6161

6162

Figure 21

RES N-D PHIT FMI CT Pho

to

Dol

Anh

Gyp

Mul

timin

Figure 23

1073 1076

Dol

Anh

Gyp

RES N-D PHIT FMI CT Pho

to

Mul

timin

Depth Core Photo ProfileCore GR

As Reported

0 60

Profile Core_GR

Shift 1 ft

0 60

-6206

-6208

-6210

-6212

-6214

-6216

-6218

-6220

-6222

-6224

-6226

-6228

-6230

-6232

-6234

Figure 25

JSR paper Barnaby revised Jan 18Figure 01Figure 02Figure 03Figure 04Figure 05Slide Number 1

Figure 06Figure 07Figure 08Slide Number 1

Figure 09Slide Number 1

Figure 10Slide Number 1

Figure 11Slide Number 1

Figure 12Figure 13Figure 14Figure 15Figure 16Figure 17Figure 18Figure 19Figure 20Figure 21Figure 22Slide Number 1

Figure 23Figure 24Slide Number 1

Figure 25