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The study of fractures and faults has long been recognized as a cornerstone of shale reservoir characterization, given their profound influence as primary storage spaces and critical seepage channels [...]

Based on the data of cores, thin sections, well logs, and test experiments, the characteristics and main controlling factors of lamellation fractures in continental shales of the third and fourth members of the Paleogene Qianjiang Formation in the Qianjiang Depression, Jianghan Basin, are studied. Lamellation fractures mainly develop along laminas in shales. They have various morphological characteristics such as straightness, bending, discontinuity, bifurcation, pinching out, and merging. Lamellation fractures with high density show poor horizontal continuity and connectivity characteristics. The average linear density of the lamellation fractures is mainly between 20 m-1 and 110 m-1, and the aperture is usually less than 160 μm. The density of lamellation fractures is related to their apertures. The smaller the apertures of lamellation fractures are, the higher the density is. The development degree of lamellation fractures is mainly controlled by mineral composition, type, thickness, density of lamination, contents of organic matter and pyrite, lithofacies, structural position, etc. Lamellation fractures develop well, especially under the conditions of medium dolomite content, large lamination density, small lamination thickness, and high total organic carbon (TOC) and pyrite contents. The influences of lithofacies on the lamellation fractures are complex. The lamellation fractures are most developed in carbonaceous layered limestone dolomite and carbonaceous layered dolomite mudstone, followed by stromatolite dolomite filled with carbonaceous pyroxene. The fractures in the massive argillaceous dolomites and carbonaceous massive mudstones are poorly developed. No fractures can be found in the carbonaceous dolomitic, argillaceous glauberites or salt rocks with high glauberite content. Structure is also an important factor controlling lamination fractures. Tectonic uplifts are beneficial to the expansion and extension of lamellation fractures, which increases fracture density. Therefore, when other influence factors are similar, lamellation fractures develop better in the high part of the structure than in the low part.

Most rock masses contain natural fractures. In many engineering applications, a detailed understanding of the characteristics of fluid flow through a fractured rock mass is critically important for design, performance analysis, and uncertainty/risk assessment. In this context, rock fractures and fracture networks play a decisive role in conducting fluid through the rock mass as the permeability of fractures is in general orders of magnitudes greater than that of intact rock matrices, particularly in hard rock settings. This paper reviews the modelling methods developed over the past four decades for the generation of representative fracture networks in rock masses. It then reviews some of the authors’ recent developments in numerical modelling and experimental studies of linear and non-linear fluid flow through fractures and fracture networks, including challenging issues such as fracture wall roughness, aperture variations, flow tortuosity, fracture intersection geometry, fracture connectivity, and inertia effects at high Reynolds numbers. Finally, it provides a brief review of two applications of methods developed by the authors: the Habanero coupled hydro-thermal heat extraction model for fractured reservoirs and the Kapunda in-situ recovery of copper minerals from fractures, which is based on a coupled hydro-chemical model.

How to reconstruct a credible three-dimensional (3D) geological model from very limited survey data, e.g. boreholes, outcrop, and two-dimensional (2D) images, is challenging in the field of 3D geological modeling. Against the limitations of the huge computational consumption and complex parameterization of geostatistics-based stochastic simulation methods, we propose an automatic reconstruction method of 3D geological models based on deep convolutional generative adversarial network (DCGAN). In this work, 2D geological sections are used as conditioning data to generate 3D geological models automatically. Various realizations can be reproduced under a same DCGAN model established through deep network training. A U-Net structure is used to enhance the fitting effect of the DCGAN model. In addition, joint loss functions are exploited to increase the similarity between 3D realizations and reference models. Three synthetic datasets were used to verify the capability of the method presented in this paper. Experimental results show that the proposed 3D automatic reconstruction method based on DCGAN can capture the features, trends and spatial patterns of geological structures well. The output models obey the used conditioning data. The complex heterogeneous structures are reconstructed more accurately and quickly by using the proposed method.

Abstract Natural fractures play an important role in controlling fluid flow and production performance, making accurate fracture zone prediction essential for petroleum exploration and development. However, prediction of fracture zones using seismic data remains difficult because fracture-related seismic responses are weak and labelled samples from wells are limited. To overcome these limitations, this study proposes a semi-supervised ladder neural network (SSLNN) for fracture zone prediction in the Asmari Formation of the A Oilfield, Iraq. Fracture development was identified from well logs, and fracture-sensitive seismic attributes were screened using support vector machine-based sensitivity analysis. Five attributes, namely variance, dip angle, curvature, azimuth angle, and dip deviation, were selected as the optimal input features. By integrating limited labelled data with abundant unlabelled seismic attribute data, the SSLNN effectively captures the nonlinear relationship between seismic responses and fracture development. The results show that the proposed method achieves an average test accuracy of 87.5%, exceeding that of the best-performing supervised model by 6.04%. Parameter analysis further indicates that model accuracy first increases, then decreases, and finally stabilises as the weight ratio between supervised and unsupervised losses increases. The prediction results reveal that fractures are more developed in Layer A than in Layer B, are stronger in the southern part of Layer A, and are mainly concentrated near structural highs and in the hanging walls of faults. These results demonstrate that the SSLNN is an effective method for fracture prediction in carbonate reservoirs with sparse labelled data.

The fracture-cave reservoirs controlled by strike-slip faults are the main targets for oil and gas exploration of ultra-deep carbonate in the Tarim Basin. It is of great significance to clarify the distribution rules of fractures related to strike-slip faults for guiding the exploration and development of ultra-deep oil and gas. In this study, six groups of strike-slip fault 3D models based on discrete element numerical simulation method have been created to investigate characteristics of fault-related fracture development and distribution law. In addition, we compared the modeling results to the measurement of fractures from the outcrop of a strike-slip fault in the Northern Tarim Basin to verify their validity. The results show that the stress environment is stable in the simple strike-slip section, and fractures intersecting with the strike-slip direction at a small angle are the principal fracture. In the releasing stepover and double-bend sections, the maximum principal stress changes from horizontal to vertical during the formation of pull-apart zones, where the principal fractures intersect the strike-slip direction at a large angle. The maximum principal stress in the restraining stepover and double-bend section remains horizontal, but their strikes change significantly with the increment of fault displacement. Thus, fractures intersecting the strike-slip direction at a small angle will become principal fractures early on, while those parallel to or anti-intersecting the strike-slip direction at a small angle will become principal fractures later. There are obvious differences in the development of fractures in different structural positions of strike-slip faults. Fractures are mainly concentrated in the fault tips, connections, and fault plane, and the magnitude of the fault damage zone is relatively larger in the first two. Compared with fault displacement, the principal damage zone (PDZ) shows stronger control on the distribution and development intensity of fractures. With the increment of fault displacement, the width of the fault damage zone and the fracture density first rapidly increases before the formation of PDZ and then slows down. Moreover, the formation time of PDZ in the restraining double-bend and stepover section is earlier than the simple strike-slip, releasing double-bend, and releasing stepover sections, and absorb more strain before the formation of the principal displacement zone. Thus, the restraining sections have the highest fracture intensity, followed by the pull-apart sections, then the simple strike-slip section. The results play an important role in understanding the development law of fractures related to strike-slip faults in different arrangements and move modes.

Percolation analysis is an efficient way of evaluating the connectivity of discrete fracture networks. Except for very simple cases, it is not feasible to use analytical approaches to find the percolation threshold of a discrete fracture network. The most commonly used percolation threshold corresponds to the occurrence of percolation on average for the set of parameters (p50), which is not adequate for applications in which a high confidence in the percolation threshold is required. This study investigates the direct relationships between the percolation threshold at low probability (p0, referred to as zero-percolation threshold) and the properties of fracture networks with one set of fractures (fractures with similar orientations) in two-dimensional domains. A generalized non-linear multivariate relationship between p0 and fracture network parameters is established based on connectivity assessments of a significant number of numerical simulations of fracture networks. A feature of this relationship is the invariant shape of marginal relationships. A comparison study with an analytical solution and applications in both synthetic and real fracture networks shows that the derived relationship performs well in fracture networks of different sizes and orientations. A significant benefit of this relationship is that, when an analytical solution is not available, it can provide fast and reliable connectivity statistics of fracture networks based only on fracture parameters.

The Sichuan Basin in south-western China is rich in shale oil in the Jurassic strata. Due to its complex geological characteristics, reservoir identification using current log-constrained seismic inversion methods is difficult. Characteristics of the shale oil reservoirs were tested on the basis of the petrophysical experimentation of core samples from the said strata. Thin sections and logging data analysis showed the influencing factors on petrophysical characteristics and clarified the sensitive geophysical parameters for reservoir identification. The Da'anzhai Member reservoirs were determined to have high acoustic velocities, Vp/Vs ratios and Young's moduli, and low Poisson's ratios. Several geological factors have influenced the petrophysical properties of the reservoirs. The Da'anzhai Member reservoirs are characterized by a low content of clay minerals and the development of fractures and laminae. The presence of clay minerals caused general high acoustic velocities of the reservoirs; the presence of fractures and laminae in high-quality reservoirs results in a decrease of the acoustic velocities. Therefore, the relatively low value against the background of high acoustic velocity can be used as the criteria for high-quality reservoirs. Poisson's ratio is obviously different in reservoirs and non-reservoirs. When it is <0.269, the reservoirs can be fully identified. In addition, the combination of the Lame constant and shear modulus (λ > 25.277 and μ > 20.72 GPa), P-wave and S-wave velocity (Vp > 4967 and Vs > 2781 m s−1), wave impedance and Vp/Vs ratio (AI > 13.319 g · cm3 · km · s−1 and Vp/Vs > 1.792) can also provide references for reservoir identification.

Acute kidney injury (AKI) is a major kidney disease characterized by an abrupt loss of renal function. Accumulating evidence indicates that incomplete or maladaptive repair after AKI can result in kidney fibrosis and the development and progression of chronic kidney disease (CKD). Hypoxia, a condition of insufficient supply of oxygen to cells and tissues, occurs in both acute and chronic kidney diseases under a variety of clinical and experimental conditions. Hypoxia-inducible factors (HIFs) are the “master” transcription factors responsible for gene expression in hypoxia. Recent researches demonstrate that HIFs play an important role in kidney injury and repair by regulating HIF target genes, including microRNAs. However, there are controversies regarding the pathological roles of HIFs in kidney injury and repair. In this review, we describe the regulation, expression, and functions of HIFs, and their target genes and related functions. We also discuss the involvement of HIFs in AKI and kidney repair, presenting HIFs as effective therapeutic targets.

Both endoplasmic reticulum (ER) stress and autophagy have been implicated in chronic kidney injury and renal fibrosis. However, the relationship and regulatory mechanisms between ER stress and autophagy under this condition remain largely unknown. In this study, we first established a mouse model of ER stress-induced chronic kidney injury by 2 weekly injections of a low dose of tunicamycin (TM), a classical ER stress inducer. This model showed the induction of ER stress, autophagy, fibrosis and apoptosis in kidney tissues. In vitro, TM also induced ER stress, autophagy, fibrosis and apoptosis in HK-2 human kidney proximal tubular cells and BUMPT-306 mouse kidney proximal tubular cells. In these cells, autophagy inhibitor suppressed TM-induced fibrotic changes and apoptosis, suggesting an involvement of autophagy in ER stress-associated chronic kidney injury. PERK inhibitor ameliorated autophagy, fibrotic protein expression and apoptosis in TM-treated cells, indicating a role of the PERK/eIF2α pathway in autophagy activation during ER stress. Similar results were shown in TGF-β1-treated HK-2 cells. Interestingly, in both TM- or TGF-β1-treated kidney proximal tubular cells, inhibition of autophagy exaggerated ER stress, suggesting that autophagy induced by ER stress provides a negative feedback mechanism to reduce the stress. Together, these results unveil a reciprocal regulation between ER stress and autophagy in chronic kidney injury and fibrosis.