Porosity enhancement potential through dolomite mineral dissolution

May 6, 2019 - Shale oil has been found in the argillaceous dolomite reservoir of the Paleogene Xingouzui Formation in the Jianghan Basin. However, the...
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Porosity enhancement potential through dolomite mineral dissolution in the shale reservoir: A case study of argillaceous dolomite reservoir in the Jianghan Basin Wenhao Li, Yufeng Kuang, Shuangfang Lu, Zehu Cheng, Haitao Xue, and Lei Shi Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.9b00486 • Publication Date (Web): 06 May 2019 Downloaded from http://pubs.acs.org on May 7, 2019

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Porosity enhancement potential through dolomite mineral

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dissolution in the shale reservoir: A case study of argillaceous

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dolomite reservoir in the Jianghan Basin

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Wenhao Lia,b, Yufeng Kuanga, b, Shuangfang Lua,b*, Zehu Chenga,b, Haitao

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Xuea,b, Lei Shic,d

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aKey

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bSchool

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cShenyang

Institute of Geology and Mineral Resources, Shenyang 110034, Liaoning, China;

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dShenyang

Center of Geological Survey, CGS, Shenyang 110034, Liaoning, China.

Laboratory of Deep Oil and Gas, China University of Petroleum (East China), Qingdao 266580, China; of Geosciences, China University of Petroleum (East China), Qingdao, Shandong 266580, China;

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ABSTRACT

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Shale oil has been found in the argillaceous dolomite reservoir of the Paleogene

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Xingouzui Formation in the Jianghan Basin. However, the shale oil storage

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mechanism in these rocks remains unclear, considering that increasing attention has

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been paid to the shales instead of the argillaceous dolomites. This article illustrated

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the microscopic pore structure and distribution of the argillaceous dolomite reservoir,

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and discussed the porosity enhancement potential through dolomite mineral

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dissolution by organic acids, and indicated the contribution of the dolomite mineral

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dissolution pores to the porosity. Scanning electronic microscope (SEM) images show

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that the argillaceous dolomite reservoirs mainly contain inorganic pores, including

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intercrystalline pores, intergranular pores and dissolution pores. However, the organic *Corresponding author at: Key Laboratory of Deep Oil and Gas, China University of Petroleum (East China), Qingdao 266580, China. E-mail: [email protected], Tel: 86-18661856596(S. Lu). 1

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pores are observed to be sporadically distributed. Nano-CT data show that the pores

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of the argillaceous dolomite vary in morphology and size and are unevenly spatially

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distributed. There are some isolated pores and unevenly distributed throats, among

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which larger throats are located in areas with well-developed pores. The pores of the

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shale reservoirs are mainly related to dolomite mineral rather than other minerals.

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With increase in dolomite mineral content, porosity and pore connectivity are

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improved, indicating that high dolomite mineral content has greatly promoted both the

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porosity and permeability of the argillaceous dolomite reservoir in the study area. The

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organic acids experiment confirmed this conclusion that the porosity enhancement

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potential by dissolution reactions is notable when the dolomite mineral content in the

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samples is over 16%. The porosity enhancement through dolomite mineral dissolution

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ranges from 0.48% to 4.85%, with an average of 2.34%. Thus, dissolution pores are

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considered to be significant reservoir space for shale oil storage in the argillaceous

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dolomite reservoir in the Paleogene Xingouzui Formation from the Jianghan Basin.

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Keywords: reservoir space; micropore structure; porosity enhancement potential; CT

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reconstruction; shale reservoir

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1. Introduction

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With reduction in conventional oil and gas resources, increasing attention has

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been paid to unconventional petroleum including but not limited to shale oil and

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gas.1-5 Research on shale oil and gas has mainly been focused on South China,

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because shales are widely distributed there. However, shale gas resources, rather than

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shale oil resources, have been found in the above region owing to the fact that the 2

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shales are mainly over-mature in the deep-buried stratums.6-11 Fortunately, shale oil

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resources have been found in the argillaceous dolomite of the Jianghan Basin in

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central China in recent years.12-14 Moreover, Pang et al.15 found that the argillaceous

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limestone and argillaceous dolomite have higher porosity and oil saturation compared

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with the mudstone in the Permian Lucaogou Formation in Jimusaer Depression of the

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Junggar Basin, which was the main target for shale oil exploration. Petersen et al.16

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proposed that the average TOC value and hydrogen index (HI) of the Upper

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Jurassic-lowermost Cretaceous argillaceous shale are ~7% and >500 mg/g,

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respectively and believed that the argillaceous shales are oil-prone. Successful

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exploration of shale oil on argillaceous dolomite not only makes the Chinese

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government begin to care about shale oil resources but also opens up a new field

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(argillaceous dolomite or dolomite mudstone) for shale oil exploration.

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Numerous studies are focusing on the pores in shale. However, researchers are

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seldom concerned with the argillaceous dolomite. There is consensus upon the fact

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that mud shale mainly contains micron-sized and nanometer-scale pores, and the latter

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prevail.7,17-25 Although most studies have pivoted around qualitative analyses of the

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storage capacity of shale,26-29 at present, quantitative technologies are increasingly

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being used to discuss shale reservoirs.30,31 The inorganic pores were also important in

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shales.32,33 Shale containing dolomite has more complicated reservoir space types

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(pore types). Many scholars have observed the existence of intracrystalline pores in

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carbonate minerals, solution pores, organic pores and cracks in shale samples by

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means of scanning electronic microscope (SEM) and thin section analysis.34-36 Their 3

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studies reveal that both shale and argillaceous dolomite are capable of developing

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organic and inorganic pores, but the latter contains more inorganic pores and more

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reservoir space types.

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Because of the high resolution of the field emission scanning electronic

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microscope (FE-SEM), scholars are increasingly choosing this method to study pore

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morphology, pore area percentages, and pore distribution.24,37,38 Ma et al.39

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quantitatively characterized graptolite-derived organic matter in the Longmaxi shale

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using SEM analysis and proposed that graptolite periderms contributed to the low

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porosity of the shale, but graptolite-derived organic matter could form an

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interconnected organic pore system in the shale. With the improvement of the

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resolution and accuracy of the technology, CT scans and focused ion beam scanning

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electron microscopy (FIB-SEM) technologies had been used more and more in the

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study of rock composition and microstructure,39-45 considering that SEM images can

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only indicate two-dimensional pore distribution. Boruah and Ganapathi46 evaluated

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the pore system and calculated the porosities of Barren Measure shales using micro

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computed tomography (μ CT). Further, the laser confocal scanning microscope has

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been used to reveal the structure of micro-pores through its layered scanning and 3D

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reconstruction technology and to calculate the surface porosity of pores with digital

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image analysis methods.47

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Previous studies on the characterization of the microscopic pore structure mostly

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considered organic pores in shales as the research objects but ignored inorganic pores

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(pores in minerals rather than in organic matter). Dolomite or lime shale reservoirs 4

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commonly contain a higher number of inorganic pores. The dolomite mineral is

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beneficial to the development of secondary pores, which is an important type of pore

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in the shale reservoirs.34 Zeng et al.48 believed that the fractures are abundant when

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the dolomite content up to 64.7% in the Niutitang Shale. The research on porosity

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enhancement potential through dolomite mineral dissolution is mainly focused on

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sandstones rather than Shales.32 Cui et al.33 considered that the maximum

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intergranular volume enhanced by early carbonate cements can reach up to 8% and

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5% for fine-grained and medium-grained sandstones, respectively. Yuan et al.49

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proposed that the selective dissolution of feldspars instead of the carbonate minerals

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(calcites and dolomites) is the way to generate secondary pores in the buried

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sandstones when the two types of dissolvable minerals are concomitant. However, the

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porosity enhancement potential through dolomite mineral dissolution by organic acids

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is still unclear, restricting the understanding of the shale oil storage mechanism in the

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argillaceous dolomite reservoir. This study took the argillaceous dolomite reservoir in

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the Xingouzui Formation of the Jianghan Basin as an example, where shale oil has

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been found in recent years, to study the microscopic pore structure and distribution of

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the argillaceous dolomite and to discuss the porosity enhancement potential through

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dolomite mineral dissolution by organic acids, as well as to indicate the contribution

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of the dolomite mineral dissolution pores to the porosity.

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2. Samples and experiments

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2.1 Samples and geological settings

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The Jianghan Basin is located in the central Jianghan flatland in the Hubei 5

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Province, central China. It is formed on a basement of Mesozoic-Paleozoic marine

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carbonates, clastics and continental coal-bearing clastics. The evolution of the basin

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experienced three stages: the early Yanshan extrusion, the Cretaceous-Paleogene rift

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depression and the Neogene-Quaternary depression, through the Yanshan and

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Himalayan movements from the Cretaceous to the Quaternary. The basin is

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characterized by several uplifts and sags. The main structural belt of the basin is

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shown in Figure 1A. In March 2012, 3 tons of shale oil per day were extracted at the

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Xingouzui Formation, as revealed by Well Xin135 in the Jianghan Basin. By the end

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of 2012, there had been 6 vertical wells and 4 horizontal wells with industrial crude

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flow. Oil and gas shows have been found in the argillaceous dolomite from the

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Xingouzui Formation in more than 100 wells so far. Among these, wells in the

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Yajiao-Xingou Uplift and the Chentuokou Sag were found to be rich in shale oil. The

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typical wells in the two above structural belts are shown in Figure 1A. Samples were

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taken from Well JX1 and Well JC1. The lithology of the Xingouzui Formation is

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mainly argillaceous dolomite, while there also developed shales in the bottom of this

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formation (Figure 1B).

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2.2 Experiments

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Both FE-SEM and Nano CT were carried out in the State Key Laboratory of

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Petroleum Resources and Prospecting of China University of Petroleum in Beijing,

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the capital of China. Samples were cut to 1 cm in size before FE-SEM observation,

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and were polished using emery paper. The polished samples were milled using Ar ion

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milling. The polishing time was 10 h and the accelerating voltage was 4 kV. Then, a 6

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conductive surface of the milled samples could be obtained after Au-plated. After that,

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the observations were performed for this experiment. The FE-SEM (FEI Quanta 200F)

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has a resolution of 1.2 nm. It is equipped with three analytic systems including

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secondary electron imaging (SE), electron backscatter diffraction (EBSD) and the

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analysis of X-ray energy spectrum. The three systems can be freely switched over

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from one to another.

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The Nano CT (ULtraXRAM-L200, Xradia, USA) in the lab was used to scan the

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samples and reconstruct images through a back-projection algorithm, using its

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preloaded software with output images in the tiff format. The resolution is 65 nm

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(both vertical and horizontal resolution), and the core scanning diameter and height

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are both 65μm. The principle of the machine can be simply described as the following:

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a set of projection data can be acquired by spinning samples with different angles in

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the X-ray beam. The source-target then calculates the attenuation coefficients of every

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element volume of the samples through a reconstruction algorithm, assigns a gray

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value, and finally gets 3-D data volume of the samples. The different composition of

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the samples can be recognized based on the difference in the X-ray adsorption

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coefficient of the component in the samples. The binary grayscale images after

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segmentation can be used to calculate parameters that describe the pore structure of

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samples by image analysis software.34 Pore and throat size were computed with

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opening method in mathematical morphology, while pore connectivity was calculated

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with the connected components algorithm.

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X-ray Diffraction (XRD), porosity and organic acid dissolution experiments were 7

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performed in a lab of China University of Petroleum in Qingdao, Shandong Province,

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China. The XRD data were collected using a Panalytical X’Pert PRO diffractometer

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with Cu Ka radiation (40 kV, 30 mA) and scanning speed of 2° 2 theta (h) per minute.

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According to the results of the XRD, eight block samples were carefully selected

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for the organic acid dissolution experiment. A mixed solution of 500 ml is configured

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with some distilled water and quantitative organic acids (1 ml analytically pure acetic

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acid, 0.28 g Colorless crystal oxalic acid and 4 to 6 drops analytically pure formic

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acid). Then, the observation and description of the microcosmic morphology

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characteristics of the eight block samples before and after treatment in a high-pressure

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reaction kettle with the above 500 ml mixed solution can be performed through the

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JEM-2100UHR transmission electron microscope (TEM).

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3. Results and discussion

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3.1 Reservoir space type in shale

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Although organic nanopores were considered to be major reservoir space in shales,

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the inorganic pores were also significant in shales.50-52 This study took the

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argillaceous dolomite in the Xingouzui Formation of the Jianghan Basin as an

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example to explore the reservoir space features of shale reservoirs. Many inorganic

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pores were observed using SEM images in the study area, and there also exist a small

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number of organic pores (Figure 2). Inorganic pores include intercrystalline pores,

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intergranular pores and solution pores (pores formed during mineral dissolution),

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among which the intercrystalline pores (mainly in dolomite) prevail (Figure 2a). They

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can also be observed in strawberry-shaped pyrite (the shape of the pyrites similar to

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the strawberry) (Figure 2b). Intergranular pores were found in layered clay particles 8

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(mainly illite) and detrital mineral particles (Figure 2c). Solution pores are another

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important pore type in the samples (Figure 2a, 2d). Organic pores were seen dispersed

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in the samples (Figure 2e, 2f). The intercrystalline pores, intergranular pores and

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solution pores show irregular shapes (Figure 2a-2d), while the morphology of the

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organic pores is approximatively circular (Figure 2e, 2f). Analyses indicate that the

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reservoir space in the study area is mainly composed of inorganic pores of various

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types. Organic pores were only detected in exceptional samples and bear less

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significance to shale oil exploration.

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3.2 Microscopic pore structure and distribution

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This study focused on mud dolomite samples from the Jianghan Basin and

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analyzed the possibility of applying CT reconstruction calibration to discuss

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microscopic pore structure and distribution. Two argillaceous dolomite samples with

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84.8% and 48.2% dolomite minerals were chosen to discuss the configuration,

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three-dimensional pore and throat distribution, and pore connectivity (Figure 3, Figure

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4). There are multiple configurations and sizes of the pores, most of the pores show

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irregular shapes while some are circular (Figure 3c, Figure 4c). The number of pores

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in the two samples is 4912 and 1762 respectively, and the pore size mainly ranges

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from 174nm to 14.25μm and from 174nm to 7.8μm, respectively, with the mean value

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of 424nm and 391nm, respectively. The spatial distribution of the pores is

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non-uniform (Figure 3d, Figure 4d). The channel length in the two samples mainly

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ranges from 92nm to 45μm and from 92nm to 15.7μm, respectively, with the mean

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value of 673nm and 530nm, respectively. The throat size distribution (width) in the 9

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above samples is in the range from 65nm to 20μm and from 65nm to 9μm,

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respectively, with the mean value of 343.6nm and 250.3nm, respectively. The

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porosities can be obtained after pore extraction, and the values for the two above

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samples are 10.12% and 1.43%, respectively, indicating that porosity is promoted by

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dolomite mineral content. Figure 3d shows that the pore connectivity in this sample is

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good, although there are some isolated and dispersed pores with bad connectivity.

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However, Figure 4d shows that most of the pores have bad connectivity. From the CT

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images of the two samples, it is revealed that the pore connectivity gets better with

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increase in dolomite mineral content.

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3.3 Contribution of dissolved pores to porosity

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3.3.1 The developmental characteristics of dissolved pores

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Here, two types of shale reservoirs, mudstones and argillaceous dolomites, are

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discussed to understand the characteristics of dissolved pores. The porosity and

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permeability have weak decreasing tendency with depth (Figure 5, Figure 6). The

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mudstones and argillaceous dolomites both have three peak areas where the porosity

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and permeability are developed (Figure 5, Figure 6), that is, there are three secondary

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pore developmental zones. Thus, the dissolved pores play an important role in the

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shale reservoir in the Jianghan Basin.

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Compared with mudstones, the argillaceous dolomite has more complex mineral

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components.34 Figure 7 shows the relationship between the mineral components and

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physical properties of argillaceous dolomite reservoirs. The clay, quartz and feldspar

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mineral contents have a negative correlation with porosity and permeability (Figure 7), 10

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indicating that pores related to these minerals are not developed. However, there is a

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positive correlation between dolomite mineral and porosity and permeability (Figure

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7). This suggests that the high content of dolomite mineral has not only enhances the

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porosity but also promotes the pore connectivity. Figure 8 shows that both

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intercrystalline pores and intergranular pores of the shale reservoirs are connected

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with dolomite minerals rather than quartz, feldspar or clay mineral. The SEM images

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also suggest that the intercrystalline and dissolved pores are the main reservoir space

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in this study area (Figure 2), and have contributed much to the porosity of the

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argillaceous dolomite reservoirs. Dissolved pores are mainly in the dolomite minerals

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instead of feldspars although there are also some dissolve pores developed in the

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feldspars (Figure 2d).

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3.3.2 Porosity enhancement potential through dolomite mineral dissolution by

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organic acids

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The development of the dolomite mineral not only improves the porosity but also

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promotes pore connectivity, which may be due to the dissolved pores in dolomite

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minerals. To indicate the contribution of dissolved pores to the porosity, eight samples

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with dolomite mineral contents ranging from 4% to 93% were chosen, and the

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porosity enhancement potential through mineral dissolution (mainly dolomite mineral)

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by organic acid was discussed. From SEM images before and after the organic acids

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experiment (Figure 9), it can be seen that the primary sample has a small number of

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dissolved pores while the solution pores are very common after the organic acid

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dissolution reaction. After the dissolution process, faveolate secondary pores were 11

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formed. With increase in the dolomite mineral content, the dissolution characteristics

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become more significant (Figure 10). Solution pores can seldom be observed when

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the samples with dolomite mineral content are below 16% after the dissolution

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reaction by organic acids (Figure 10). However, with increase in the dolomite mineral,

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the rock surface was dissolved under the effect of organic acids, and the porosity

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enhancement potential is notable (Figure 10). The residual clay minerals caused by

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dissolution can be observed through SEM images (Figure 10).

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3.3.3 Quantitative characterization of dissolution pores

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McCreesh et al.53 determined that the areal porosity of thin section images can be

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equal to the actual porosity. Therefore, the porosity of dissolved pores can be

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approximately calculated by the ratio between the pore area of dissolution pores and

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the viewed area in its SEM images. This article focuses on approximate calculation of

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dissolution porosity using the average ratio at a certain depth under different

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magnifications in the SEM images.

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Figure 11 shows the procedure for SEM calibration: First, differentiate and mark

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out dissolution pores in the SEM images using the analysis software. Second, obtain

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the porosity of the dissolution pores by computing the actual pore area and the viewed

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area in the images. The dissolution porosity mainly contributed by dissolved pores in

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dolomite minerals can reach from 0.48% to 4.85%, with an average of 2.34% (Table

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1). Thus, dissolved pores are an important type of reservoir space in the study area

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due to their high dolomite content. Argillaceous dolomites with high TOC contents13

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can generate abundant organic acids, which promotes the dissolution reaction. 12

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4. Conclusion

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(1) The shale reservoirs in the Xingouzui Formation of the Jianghan Basin contain

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mostly inorganic pores, including intracrystalline pores, intergranular pores and

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dissolution pores.

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(2) Nano-CT three-dimensional reconstructions of pores reveal that heterogeneity

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exists in terms of pore morphology and size. Areas with well-developed pores were

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observed to have larger throats. The dolomite minerals mainly contributed to the pores

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of the shale reservoirs. High dolomite mineral content not only greatly improves the

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porosity of argillaceous dolomite but also enhances pore connectivity.

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(3) The dissolved pores, related to the dolomite mineral content, are the primary

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reservoir space in the shale-hosted oil reservoir in the study area. The organic acid

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experiment suggests that when the dolomite content is over 16%, the porosity of the

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dissolved pores is greatly promoted. The porosity enhancement through dolomite

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mineral dissolution can even reach 4.85%, with an average of 2.34%.

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Acknowledgements

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This study was financially supported by the National Natural Science Foundation

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of China (41172134), the Research Project Funded by SINOPEC (P15028).

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References

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(1) Hill, D. G.; Lombardi, T. E.; Martin, J. P. Northeastern Geology and

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Environmental Sciences. 2004, 26, 57-78. (2) Perry, K.; Lee, J. Unconventional gas reservoirs: tight gas, coal seams, and shales. Washington: National Petroleum Council; 2007.

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(3) Zou, C. N.; Yang, Z.; Cui, J. W.; Zhu, R. K.; Hou, L. H.; Tao, S. Z.; Yuan, X. J.;

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Wu, S. T.; Lin, S. H.; Wang, L.; Bai, B.; Yao, J. L. Petroleum Exploration and 13

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Development. 2013, 40, 15-27. (4) Luo, Q. Y.; Gong, L.; Qu, Y. S.; Zhang, K. H.; Zhang, G. L.; Wang, S. Z. Fuel. 2018, 234, 858-871. (5) Han, H.; Pang, P.; Li, Z. L.; Shi, P. T.; Guo, C.; Liu, Y.; Chen, S. J.; Lu, J. G.; Gao, Y. Marine and Petroleum Geology. 2019, 100, 270-284. (6) Han, S. B.; Zhang, J. C.; Li, Y. X.; Horsfield, B.; Tang, X.; Jiang, W. L.; Chen, Q. Energy & Fuels. 2013, 27, 2933-2941. (7) Luo, Q. Y.; Zhong, N. N.; Dai, N.; Zhang, W. International Journal of Coal Geology. 2016, 153, 87-98. (8) Luo, Q. Y.; Hao, J. Y.; Skovsted, C. B.; Luo, P.; Khan, I.; Wu, J. International Journal of Coal Geology. 2017, 183, 161-173. (9) Luo, Q. Y.; Hao, J. Y.; Skovsted, C. B.; Xu, Y. H.; Liu, Y.; Wu, J.; Zhang, S. N.; Wang, W. L. International Journal of Coal Geology. 2018, 195, 386-401. (10) Han, H.; Cao, Y.; Chen, S. J.; Lu, J. G.; Huang, C. X.; Zhu, H. H.; Zhan, P.; Gao, Y. Fuel. 2016, 186, 750-757. (11) Han, H.; Zhong, N. N.; Ma, Y.; Huang, C. X.; Wang, Q.; Chen, S. J.; Lu, J. G. Journal of Natural Gas Science and Engineering. 2016, 33, 839-853.

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(13) Li, W. H.; Lu, S. F.; Xue, H. T.; Zhang, P. F.; Wu, S. Q. Marine and Petroleum

309 310 311 312 313 314 315

Geology. 2015, 67, 692-700. (14) Li, W. H.; Lu, S. F.; Xue, H. T.; Zhang, P. F.; Hu, Y. Fuel. 2016, 181, 1041-1049. (15) Pang, H.; Pang, X. Q.; Dong, L.; Zhao, X. Journal of Petroleum Science and Engineering. 2018, 163, 79-90. (16) Petersen, H. I.; Hertle, M.; Sulsbrück, H. International Journal of Coal Geology 2017, 173, 26-39.

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(17) Reed, R. M.; Loucks, R. G. AAPG Annual Convention Abstracts. 2007, 16, 115.

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(18) Jarvie, D. M. Unconventional Shale Resource Plays: shale-Gas and shale-Oil

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Opportunities. Fort Worth Business Press meeting; 2008. (19) Ambrose, R. J.; Hartman, R. C.; Diaz-Campos, M.; Akkutlu, I. Y.; Sondergeld, 14

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C.H. New pore-scale considerations for shale gas in place calculations. SPE,

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131772 ; 2010.

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(20) Zou, C. N.; Zhu, R. K.; Bai, B.; Yang, Z.; Wu, S. T.; Su, L.; Dong, D. Z.; Li, X. J. Acta Petrologica Sinica. 2011, 27, 1857-1864 (in Chinese with English Abstract). (21) Curtis, M. E.; Sondergeld, C. H.; Ambrose, R. J.; Rai, C. S. AAPG Bulletin. 2012, 96, 665-677. (22) Chalmers, G. R.; Bustin, R. M.; Power, I. M. AAPG Bulletin. 2012, 96, 1099-1119. (23) Zhu, R. F.; Zhang, L. Y.; Li, J. Y.; Li, Z.; Liu, Q.; Wang, X. H.; Wang, R.; Wang,

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J. Petroleum Geology & Experiment. 2012, 34, 352-356 (in Chinese with English

330

abstract).

331 332 333 334 335 336

(24) Milliken, K. L.; Rudnicki, M.; Awwiller, D. N.; Zhang, T. W. AAPG Bulletin. 2013, 97, 177-200. (25) Haeri-Ardakani, O.; Al-Aasm, I; Coniglio, M. Marine and Petroleum Geology. 2013, 43, 409-422. (26) Ross, D. J. K.; Bustin, R. M. Bulletin of Canadian Petroleum Geology. 2007, 55, 51-75.

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(27) Ruppel, S. C.; Loucks, R. G. The Sedimentary Record. 2008, 6, 4-8.

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(28) Slatt, R. M.; O'Brien, N. R. AAPG Bulletin. 2011, 95, 2017-2030.

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(29) Lu, S. F.; Chen, F. W.; Xiao, H.; Li, J. Q.; He, X. P. Quantitative

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characterization of organic and inorganic pore in shales—take the Niutitang

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Formation in the Lower Cambrian of the Qiannan depression. Nanjing: The 14th

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Chinese society for mineralogy. petrology and geochemistry; 2013 (in Chinese).

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(30) Loucks, R. G.; Reed, R. M.; Ruppel, S. C.; Jarvie, D. M. Journal of Sedimentary Research. 2009, 79, 848-861.

345

(31) Modica, C. J.; Lapierre, S. G. AAPG Bulletin. 2012, 96, 87-108.

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(32) Higgs, K. E.; Funnell, R. H.; Reyes, A. G.; Marine and Petroleum Geology. 2013,

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(34) Li, W. H.; Wang, W. M.; Lu, S. F.; Xue, H. T. Fuel. 2017, 206, 690-700.

351

(35) Sonnenberg, S. A.; Pramudito, A. AAPG Bulletin. 2009, 93, 1127-1153.

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(36) Deng, M. Y.; Liang, C. Earth Science Frontiers. 2012, 19, 173-181 (in Chinese

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with English abstract). (37) Milliken, K. L.; Ko, L. T.; Pommer, M.; Marsaglia, K. M. Journal of Sedimentary Research. 2014, 84, 961-974.

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(38) Pommer, M.; Milliken, K. AAPG Bulletin. 2015, 99, 1713-1744.

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(39) Ma, Y.; Zhong, N. N.; Cheng, L. J.; Pan, Z. J.; Dai, N.; Zhang, Y.; Yang, L.

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Marine and Petroleum Geology. 2016, 72, 1-11.

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(40) Bera, B.; Mitra, S. K.; Vick, D. Micron. 2011, 42, 412-418.

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(41) Wu, S. T.; Zhu, R. K.; Cui, J. G.; Cui, J. W.; Bai, B.; Zhang, X. X.; Jin, X.; Zhu,

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D. S.; You, J. C.; Li, X. H. Petroleum Exploration and Development. 2015, 42,

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185-195.

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(42) Li, J. J.; Yin, J. X.; Zhang, Y. N.; Lu, S. F.; Wang, W. M.; Li, J. B.; Chen, F. W.; Meng, Y. L. International Journal of Coal Geology. 2015, 152, 39-49.

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(44) Long, H. L.; Swennen, R.; Foubert, A.; Dierick, M.; Jacobs, P. Sedimentary

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Geology. 2009, 220, 116-125. (45) Bai, B.; Zhu, R. K.; Wu, S. T.; Yang, W. J.; Gelb, J.; Gu, A.; Zhang, X. X.; Su, L. Petroleum Exploration and Development. 2013, 40, 354-358. (46) Boruah, A.; Ganapathi, S. Journal of Natural Gas Science and Engineering. 2015, 26, 427-437. (47) Sun, X. D.; Li, Y. Q.; Dai, Q. W. Journal of Chinese Electron Microscopy Society. 2014, 33, 123-128 (in Chinese with English abstract). (48) Zeng, W. T.; Zhang, J. C.; Ding, W.L.; Zhao, S.; Zhang, Y. Q.; Liu, Z. J.; Jiu, K. Journal of Asian Earth Sciences. 2013, 75, 251-266. (49) Yuan, G. H.; Cao, Y. C.; Jia, Z. Z.; Gluyas, J.; Yang, T. Marine and Petroleum Geology. 2015, 60, 105-119.

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(50) Elgmati, M. Shale gas rock characterization and 3D submicron pore network

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reconstruction. Rolla: Missouri University of Science and Technology; 2011. 16

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(51) Nie, H. K.; Zhang, J. C. Types and characteristics of shale gas reservoir: A case

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study of Lower Paleozoic in and around Sichuan Basin. Petroleum Geology &

382

Experiment. 2011, 33, 219-232 (in Chinese with English abstract).

383

(52) Yang, F.; Ning, Z. F.; Hu, C. P.; Wang, B.; Peng, K.; Liu, H. Q. Characterization

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of microscopic pore structures in shale reservoirs. Acta Petrolei Sinica. 2013, 34,

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301-311 (in Chinese with English abstract).

386 387

(53) McCreesh, C. A.; Ehrlich, R.; Crabtree, S. J. AAPG Bulletin. 1991, 75, 1563-1578.

388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 17

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410 411 412

413 414

Figure 1. (A) The location of the structural belts and typical wells in the Jianghan

415

Basin. (B) The comprehensive stratigraphic column of the Xingouzui Formation in

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the Jianghan Basin.

417 418 419 420 421 422 423 424 425 426 427 18

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428 429

430 431

Figure 2. Reservoir space of shale reservoir in the Xingouzui Formation of the

432

Jianghan Basin (The pictures of a, b, c and d are from Li et al.14).

433

Note: a. intercrystalline pores in the dolomicrite, Well JC1, 2195.85m, argillaceous

434

dolomite, SEM×10000; b. intercrystalline pores in the strawberry pyrite aggregates,

435

Well JX1, 1464m, argillaceous dolomite, SEM×10000; c. Intergranular pores in the

436

detrital mineral particles, Well JX1, 1393.3m, argillaceous dolomite, SEM×8000; d.

437

Dissolved pores in the feldspars, Well JX1, 1464m, argillaceous dolomite, SEM ×

438

20000; e. organic pores, Well JX1, 1442.85m, mudstone, SEM × 3000; f.

439

microfractures, Well JC1, 2191.9m, argillaceous dolomite, SEM×4000.

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440 441

Figure 3. CT image process steps (Well JC1, 2195.9m, argillaceous dolomite, with the

442

content of dolomite mineral 84.8%).

443

Note: (a) two dimensional segments; (b) two dimensional data; (c) three dimensional

444

data; (d) three dimensional pore distribution and pore connectivity (The connected

445

pores were marked in one color).

446 447 448 449 20

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450 451

Figure 4. CT image process steps (Well JC1, 2117.0m, argillaceous dolomite, with the

452

content of dolomite mineral 48.2%).

453

Note: (a) two dimensional segments; (b) two dimensional data; (c) three dimensional

454

data; (d) three dimensional pore distribution and pore connectivity (The connected

455

pores were marked in one color).

456 457

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458 459

Figure 5. Vertical distribution of porosity of the shale reservoirs in the Xingouzui

460

Formation from the Jianghan Basin.

461 462 463 464 465 466 467 468 22

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469 470

Figure 6. Vertical distribution of permeability of the shale reservoirs in the Xingouzui

471

Formation from the Jianghan Basin.

472 473 474 475 476 477 478 479 23

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480 481

Figure 7. Relationship between mineral components and porosity and permeability of

482

the argillaceous dolomite reservoirs from the Jianghan Basin.

483 484 485 486 487 488 489 24

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490 491

Figure 8. Percentage content of the pore types contributed by mineral composition of

492

the shale reservoirs in the Jianghan Basin (the number of SEM pictures: 98; the

493

number of pores: 7610).

494 495 496 497 498 499 500 501 502 503 504 505 25

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506 507

Figure 9. SEM images of JH21 (Well JC1, 2191.0m, argillaceous dolomite, with

508

dolomite mineral content 86%) showing the characteristics of dissolved pores before

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(the upper two images) and after (the following two images) organic acids

510

experiment.

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518 519

Figure 10. SEM images showing the characteristics of dissolved pores in the

520

argillaceous dolomite in the Xingouzui Formation from the Jianghan Basin after

521

dissolution reaction (the percentage represents dolomite mineral content).

522 523 524 525 526 527 528 529 530 531 532 533

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534 535

Figure 11. SEM images showing calibration of dissolved pores in the argillaceous

536

dolomite in the Xingouzui Formation from the Jianghan Basin.

537 538 539 540 541 542 543 544 545 546 547 548 549 28

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Energy & Fuels

550

Table 1

551

Dissolution porosity of the argillaceous dolomite reservoir in the Xingouzui

552

Formation from the Jianghan Basin. Well

Depth, m

Dolomite content, %

JX1

1394.1

10.3

JX1

1428.3

0.2

JX1

1392.8

11.9

JX1

1414.7

21.7

JX1

1464.0

84.2

JC1

2116.3

10.1

JC1

2117.1

48.0

JC1

2156.9

4.3

Magnification

Dissolution porosity, %

10000 20000 8000 20000 6000 10000 6000 9000 20000 10000 5000 10000 2000 5000 5000 10000

0.53 1.91 1.05 1.45 1.36 1.14 3.61 3.35 1.64 1.18 5.06 4.63 4.73 4.82 0.57 0.39

553

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Average dissolution porosity, % 1.22 1.25 1.24 3.48 1.41 4.85 4.78 0.48