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The U.S. Environmental Protection Agency’s (EPA) Superfund—the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) database—has collected and built an open-source database based on nearly 2000 US soil remediation cases since 1980, providing detailed information and references for researchers worldwide to carry out remediation work. However, the cases were relatively independent to each other, so the whole database lacks systematicness and instructiveness to some extent. In this study, the basic features of all 144 soil remediation projects in four major oil-producing states (California, Texas, Oklahoma and Alaska) were extracted from the CERCLA database and the correlations among the pollutant species, pollutant site characteristics and selection of remediation methods were analyzed using traditional and machine learning techniques. The Decision Tree Classifier was selected as the machine learning model. The results showed that the growth of new contaminated sites has slowed down in recent years; physical remediation was the most commonly used method, and the probability of its application is more than 80%. The presence of benzene, toluene, ethylbenzene and xylene (BTEX) substances and the geographical location of the site were the two most influential factors in the choice of remediation method for a specific site; the maximum weights of these two features reaches 0.304 and 0.288.

Natural gas hydrates (NGHs) are regarded as a new energy resource with great potential and wide application prospects due to their tremendous reserves and low CO2 emission. Permeability, which governs the fluid flow and transport through hydrate-bearing sediments (HBSs), directly affects the fluid production from hydrate deposits. Therefore, permeability models play a significant role in the prediction and optimization of gas production from NGH reservoirs via numerical simulators. To quantitatively analyze and predict the long-term gas production performance of hydrate deposits under distinct hydrate phase behavior and saturation, it is essential to well-establish the permeability model, which can accurately capture the characteristics of permeability change during production. Recently, a wide variety of permeability models for single-phase fluid flowing sediment have been established. They typically consider the influences of hydrate saturation, hydrate pore habits, sediment pore structure, and other related factors on the hydraulic properties of hydrate sediments. However, the choice of permeability prediction models leads to substantially different predictions of gas production in numerical modeling. In this work, the most available and widely used permeability models proposed by researchers worldwide were firstly reviewed in detail. We divide them into four categories, namely the classical permeability models, reservoir simulator used models, modified permeability models, and novel permeability models, based on their theoretical basis and derivation method. In addition, the advantages and limitations of each model were discussed with suggestions provided. Finally, the challenges existing in the current research were discussed and the potential future investigation directions were proposed. This review can provide insightful guidance for understanding the modeling of fluid flow in HBSs and can be useful for developing more advanced models for accurately predicting the permeability change during hydrate resources exploitation.

In this study, a 3D multicomponent multiphase simulator with a new fracture characterization technique is developed to simulate the enhanced recovery of coalbed methane. In this new model, the diffusion source from the matrix is calculated using the traditional dual-continuum approach, while in the Darcy flow scale, the Discrete Fracture Model (DFM) is introduced to explicitly represent the flow interaction between cleats and large-scale fractures. For this purpose, a general formulation is proposed to model the multicomponent multiphase flow through the fractured coal media. The S&D model and a revised P&M model are incorporated to represent the geomechanical effects. Then a finite volume based discretization and solution strategies are constructed to solve the general ECBM equations. The prismatic meshing algorism is used to construct the grids for 3D reservoirs with complex fracture geometry. The simulator is validated with a benchmark case in which the results show close agreement with GEM. Finally, simulation of a synthetic heterogeneous 3D coal reservoir modified from a published literature is performed to evaluate the production performance and the effects of injected gas composition, well pattern and gas buoyancy.

Unconventional shale gas production is often characterized by a short period of high production followed by a rapid decline in the production rate. Given the high costs of hydraulic fracturing and horizontal drilling, it is critical to identify the mechanisms behind the production loss. The existing shale gas production models often assume constant matrix permeability. However, laboratory observations show that matrix permeability can decrease significantly with increasing effective stress, which highlights the necessity of considering the stress-dependent properties of shale matrix in production analysis. Moreover, the compaction of pore space will also increase the matrix permeability by enhancing the gas-slippage effect. In this paper, a matrix permeability model which couples the effect of pore volume compaction and non-Darcy slip flow is derived. Numerical simulations are conducted to understand the role of matrix permeability evolution during production. Changes of fractures’ permeability and contact area during depletion process are also taken into account. The results indicate that the loss of fracture permeability has a greater impact at the early stage of the depletion process, while matrix permeability evolution is more important for the long-term production.

In recent years, the discovery of two gas fields in the fourth member of the Leikoupo Formation in the Western Sichuan Basin of SW China confirmed the exploration potential of microbial carbonates. The aim of the present study is to clarify the formation mechanism of the microbial reservoirs in the Leikoupo Formation. For this purpose, lithofacies, depositional environments, and diagenesis analyses were performed in samples collected from cores of 12 wells. The climate of study area was arid during Anisian time, and the water body was restricted. In such a climate, an evaporitic environment was developed, where ten types of lithofacies, dominated by microbial carbonates and gypsum rocks, were recognized. Thrombolites and stromatolites are the main high-quality reservoirs rock types in the fourth member of the Leikoupo Formation in the Western Sichuan Basin of SW China, which developed as microbial mounds, with reservoir space of microbial inter-clot pores, intra-clot pores, fenestral pores, inter-crystalline pores, and cracks. The microbial inter-clot pores are the main reservoir space, formed by trapping and binding of marls by benthic microbial communities. These pores were partially filled with evaporites because of the arid climate, which were subsequently dissolved (mainly gypsum) in the syn-depositional period, thus greatly improving the quality of reservoirs. Although some pores were occluded by multi-stage cements during the burial stage, major pores were well preserved own to the early dolomitization, rapid burial of the Leikoupo Formation, and early charging of hydrocarbon. The early dolomitization enhanced the anti-compaction ability of microbial carbonates during the burial stage. Rapid burial of the Leikoupo succession slowed down early cementation, and it also accelerated the maturation and expulsion process source rock to promote early charging of hydrocarbon in pores, which created a closed system, inhibiting strong burial cementation.