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Fractal characteristics of lacustrine tight carbonate nanoscale reservoirs Qilu Xu, Yongsheng Ma, Bo Liu, Xinmin Song, Linkai Li, Jinze Xu, Jiao Su, Keliu Wu, and Zhangxin Chen Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.7b02625 • Publication Date (Web): 11 Dec 2017 Downloaded from http://pubs.acs.org on December 12, 2017

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Fractal characteristics of lacustrine tight carbonate nanoscale reservoirs ⊥ Qilu Xu†,‡,§, Yongsheng Ma†,‡, Bo Liu‡, Xinmin Songǁ, Linkai Li*,§, , Jinze Xu§, Jiao Su†,‡, Keliu Wu§,

Zhangxin Chen§ †

School of Earth Sciences and Resources, China University of Geosciences-Beijing, Beijing 100083,

People’s Republic of China ‡

Oil and Gas Research Center, Peking University, Beijing 100871, People’s Republic of China

§

Chemical and Petroleum Engineering, University of Calgary, Calgary, Alberta T2N1N4, Canada



PetroChina Research Institute of Petroleum Exploration and Development, Beijing 100083,

People’s Republic of China ⊥

School of Petroleum Engineering, China University of Petroleum-Beijing, Beijing, 102249,

People’s Republic of China ABSTRACT: :The complexity and heterogeneity of pore structure greatly affect gas-liquid accumulation and transport, and the fractal theory has been proven to be an effective approach for studying nanoscale reservoirs in shale, coal, and tight sandstones. However, researches on fractal characteristics and control mechanisms for the lacustrine tight carbonate have received little attention. Lacustrine tight carbonate samples from the Jurassic Da'anzhai Member in the Sichuan Basin in China were systematically investigated focusing on the fractal characteristics and control mechanisms of storage spaces, minerals, diagenesis, and paleoenvironments. The fractal dimensions

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can be separated into two different and valid parts including D1 (2.515-2.785, average 2.652) and D2 (2.424-2.562, average 2.485) and the correlation between them is negative rather than positive. The average pore diameters (APD) exhibit a positive correlation with D1 and a negative correlation with D2, and the storage space is positively correlated with D2 and negatively correlated with D1. Terrigenous minerals (e.g., quartz and clay) exhibit a positive correlation with D2 and a negative correlation with D1, whereas the effects of authigenic CaCO3 minerals (e.g., calcite and aragonite) are exactly opposite to that of terrigenous minerals, which is due to the diagenesis and the own characteristics of minerals. CaCO3 minerals can effectively change pore structures and fill the storage spaces (>5nm) by cementation, compaction, pressure-solution, recrystallization, and replacement, whereas terrigenous minerals own developed irregular intra-particle pores, inter-particle pores, and micro-cracks. The low salinity and the humid (rainy) paleoclimate are favorable for the formation of terrigenous minerals (elements), whereas they are harmful to the formation of authigenic minerals (elements), which increases D2 and reduces D1. Additionally, paleoredox has a weak influence on the fractal dimensions. Keywords: Lacustrine tight carbonate; Fractal characteristics; Diagenesis; Paleoenvironments; Minerals; Nanoscale reservoirs.

1. INTRODUCTION Unconventional oil and gas reservoirs have been the major focus of exploration and development in the world.1-6 Previous studies have pointed out that studies for the unconventional reservoirs have been expanded to the nanoscale, and pore structures have effective impact on gas-liquid accumulation and transport in reservoirs (adsorption, desorption, and diffusion).1-7 Unconventional nanoscale reservoirs have more complex pore structures than conventional reservoirs, which causes high heterogeneity of reservoir properties and leads to more complicated gas-liquid accumulation and transport mechanisms.1-7 Therefore, revealing the complexity and

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heterogeneity of nanoscale reservoirs is important for unconventional reservoirs studies.5-8 There are lots of experimental methods which can be used to determine pore structure, and these methods have different advantages and disadvantages. For example, scanning electron microscope (SEM), as a widely used method of qualitative observation, can clearly observe the micro-nano pores, but its observed area is limited, and the resolution is low when the observed pore size is below 6 nm diameter.9,10 Some quantitative experimental methods including mercury injection capillary pressure (MICP), gas adsorption (CO2 or N2) and nuclear magnetic resonance (NMR) are widely used to determine the characteristics of pore structure. But these methods lack the reservoir morphology information. In addition, these methods own lots of complicated parameters with uniform standards, which makes the comparisons of different reservoirs be difficult.9-11 In short, directly revealing the complexity and heterogeneity of reservoirs only using experimental analyses is partial and inefficient.8,9 At first, the description of pore heterogeneity is often treated as a planar geometry problem in the field of surface science, but this method needs a large number of model parameters, and these parameters are very different with the actual application.9-11Subsequently, fractal theory, as a nonlinear mathematical theory, was founded by a French mathematician named Mandelbrot in the 1970s.12,13 Unlike experimental methods and planar geometry, the fractal theory can take the complicated pore structures as a whole and then quantitatively evaluate the reservoir heterogeneity.14-17 The fractal theory with the core concept of self-similarity can reflect the complexity and heterogeneity of pore surface or structure by regarding them as a value between 2 (a totally irregular or rough surface) and 3 (a perfectly smooth surface).15,16,44 The high fractal dimension value represents a complex pore structure which makes gas adsorption, diffusion and flow more difficult.5,8,15,18-21, Based on these advantages of fractal theory, it has been a widely used and effective approach for studying the complexity and heterogeneity of reservoirs. The previous studies of the fractal theory mainly focused on nanoscale reservoirs of marine shale,5,8,18 lacustrine shale,18,19 coal,20, 21 and tight sandstones6, 21,22.The lacustrine tight carbonate

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reservoir, as an important unconventional reservoir, has received little attention, and the fractal characteristics and their control mechanisms are still obscured.5-7, 24-28 First, compared with marine carbonates, the studies for lacustrine tight carbonates are limited.24,25,28-30 Lacustrine carbonate rocks are widely distributed reservoirs in many regions such as Africa, South America, Southeast Asia and East Asia.24,26,27,30 Especially, there was a breakthrough in the development of lacustrine tight carbonate reservoirs in the Jurassic Da’anzhai Member in the Fuling area, Sichuan Basin, China, indicating the important research significance.26 Second, lacustrine carbonate rocks are different from other rocks including shale, sandstone, coal, and even marine carbonate.24,25,28-30 Lacustrine carbonates are formed in unique paleoenvironments which differ from other rock types in terms of a water depth, energy, media, biological effects, provenance, and mineralogy and strongly influence the reservoirs. 24,25,28-30 Third, lacustrine carbonate is one kind of chemical sedimentary rock with dominant CaCO3 minerals and complex terrigenous minerals, which is easily influenced by diagenesis.24,29 In summary, the research for lacustrine tight carbonates is necessary and important. Therefore, our major objectives are to apply the fractal theory to investigate the complexity and heterogeneity of lacustrine tight carbonate reservoirs and find similarities and differences from other rocks. Meanwhile, based on the low temperature N2 adsorption/desorption (LTNA), X-ray diffraction (XRD), X-ray fluorescence (XRF), and carbon and oxygen isotopes experiments, relationships between nanopore structure parameters, minerals, paleoenvironments and fractal characteristics are systematically investigated. Especially, we explored the controlling mechanisms of the diagenesis of different minerals on fractal characteristics by some experiments including SEM, polarized light microscopy, fluorescence microscope and cathodoluminescence microscope.

2. MATERIALS and METHODOLOGY The Jurassic Da’anzhai Member in the Sichuan Basin is one of the most representative lacustrine tight carbonate formations in China, and test samples were chosen from this area’s typical

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wells (Table 1). To determine reservoir evaluations, the LTNA test was used to characterize samples’ nanoscale pores by an ASAP2020M device at the College of Chemistry and Chemical Engineering of the China University of Petroleum (Beijing) following the ISO 15901.2-2006 test method,31, 32 and it can get some basic parameters, such as a Barrette-Joynere-Halenda (BJH) pore volume (VBJH), a Brunauer-Emmette-Teller (BET) specific surface area (SBET), an average pore diameter (APD), and adsorption/desorption isotherm. For image qualitative evaluations, an INCA-synergy system was used to analyze the reservoir surface features via SEM and the mineral composition via energy dispersive spectrometry (EDS) at the Key Laboratory of Orogenic Belts and Crustal Evolution in Peking University. Before scanning, samples were polished by Ar-iron milling to obtain a smooth surface for getting clearer images. Polarized light microscopy, fluorescence microscope, and cathodoluminescence microscope were used to evaluate the pore structures and mineral diagenesis in China University of Geosciences (Beijing) and Peking University. For geochemistry analyses, all samples were first analyzed to determine the bulk mineralogy via XRD at the Key Laboratory of Orogenic Belts and Crustal Evolution in Peking University. Samples for the element analysis were tested by XRF spectrometry using an ADVANT’XP+ analyzer at the Key Laboratory of Orogenic Belts and Crustal Evolution in Peking University. Carbon and oxygen isotopes tests were finished using the IsoPrime 100 instrument at the School of Archaeology and Museology in Peking University based on the VPDB standard.33-39

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3. RESULTS AND DISCUSSION 3.1. Fractal Dimension Validity of Lacustrine Tight Carbonate Nanoscale Reservoirs

3.1.1 Fractal Theory and Fractal Dimensions of Lacustrine Tight Carbonate.

Figure 1. Plots of ln(V/V0) versus ln(ln (P0/P)) from the FHH model using LTNA data. Various techniques and models have been used to study the structure and fractal characteristics of reservoirs mainly including Langmuir models,40, 41 fractal BET models,42,43 fractal Frenkel-Halsey-Hill (FHH) models, 15,16,44 the thermodynamic method,16,45 image qualitative evaluations,46 small angle X-ray scattering,14, 47 MICP,32, 48-50 LTNA5,8,18-21 and NMR29, 51,52. Among these methods, the FHH model using LTNA adsorption data has been widely used to show the heterogeneity of irregular pore structures.5,7,8,10, 18-21,15,44The fractal dimension can be calculated by 6

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the published FHH model equation15,16,44: ln(V/V0)= Aln(ln(P0/P))+C

(1)

where V represents the adsorbed gas volume at the equilibrium pressure (cm3/g), V0 represents the volume of a monolayer cover of gas (cm3/g), P0 represents the saturated vapor pressure of nitrogen (MPa), and P represents the equilibrium pressure (MPa). A is the curve slope which is controlled by the adsorption mechanism and the fractal characteristics. C represents a constant. If pores are fractal, the fractal dimension D can be derived from the line slope A and it can be calculated by equation (2): A=D-3

(2)

The fractal dimension is determined by the geometrical irregularities and roughness of pore surface or structure, and a higher fractal dimension indicates a more complicated pore structure or irregular pore surface. Based on the FHH model, the curves of ln(V/Vo) versus ln(ln(P/Po)) can be divided into two parts including 0