A novel type of neural networks for feature engineering of geological data: Case studies of coal and gas hydrate-bearing sediments

Jiang, Lishuai; Zhao, Yang; Golsanami, Naser; Chen, Lianjun; Yan, Weibo

doi:10.1016/j.gsf.2020.04.016

Cited by 42 publications

(16 citation statements)

References 74 publications

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“…Microfractures, as a bridge between micropores and macrofractures, play an important role in the flow of shale oil and gas. Microfractures are the preferred channel for hydrocarbon seepage at the microscale and provide space for shale gas storage 47‐49 . The fractures are developed in three patterns: microfractures in organic matter, microfractures in inorganic matter, and microfractures between organic matter and inorganic minerals (Figure 7E‐H).…”

Section: Resultsmentioning

confidence: 99%

A 3D FIB‐SEM technique for quantitative characterization of oil shale's microstructure: A case study from the Shahejie Formation in Dongying Depression, China

Zhao

Dong

Zhang

et al. 2020

Energy Science & Engineering

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Investigating the pore structure of shale rocks plays an important role in understanding the mechanism of shale oil accumulation and migration; thus, it has a notable influence on the exploration and development of shale oil resources. In the present study, the microstructure of oil shale samples extracted from the Shahejie Formation in the Dongying Depression was investigated through the joint usage of focused ion beam (FIB) and scanning electron microscopy (SEM). Herein, we selected four representative samples. The SEM images of the sample surfaces milled by FIB indicated that pores were found in both the organic and inorganic matter. Organic pores were less developed in the samples because of the low thermal maturity of the organic matter. Continuous 3D digital rock images of shale samples were generated by FIB grinding and SEM in situ imaging. Based on multithreshold segmentation, the shale rocks were separated into different parts including kerogen, inorganic matter, and pores. The pore connectivity and pore size distributions were analyzed via Avizo software and in‐house developed MATLAB scripts. The pore size and corresponding volume distributions suggested that mesoscale pores (2‐50 nm) were abundant in the samples but they contributed limitedly to the total pore volume. Macropores (>50 nm) accounted for a small proportion but they had a greater contribution to the overall pore space volume. The coordination numbers of the subject four samples were mainly 0 and 1, which means that isolated pores accounted for the vast majority of the pores. These observations are critical to conduct reliable petrophysical simulations in the oil shales and understand their intrinsic properties accurately.

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Section: Resultsmentioning

confidence: 99%

A 3D FIB‐SEM technique for quantitative characterization of oil shale's microstructure: A case study from the Shahejie Formation in Dongying Depression, China

Zhao

Dong

Zhang

et al. 2020

Energy Science & Engineering

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“…In addition the measures of reperforation, well conversion, sidetrack drilling, infill production drilling, the recommended strategy suggested an initial injection-production ratio of 2.0 that followed by a reduced ratio of 1.0 and a 60% gas recycling at X-8. The authors would like to suggest the application of machine learning [19,20] and two other people's paper about fluid saturation+machine learning (that you can find online) for better understanding integrating all the aforementioned measures and taking into consideration the sensitivity analysis results. Table 13 lists the simulated results of the whole field from the recommended plan, while tab.…”

Section: Resultsmentioning

confidence: 99%

Simulating the strategies of oil field development for enhanced oil recovery

et al. 2020

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Many years have passed in oil field development but primary challenges faced by the X reservoir are the rapid decline of formation pressure and the significant solution gas released from the formation, which impairs production. Based on these challenges, a compositional simulation model of the X reservoir was constructed and run to establish the future development plans. The basic reservoir data collection and processing, quality assurance of the data, characteristic pressure-volume-temperature (PVT) matching by ECLIPSE PVTi, and simulation of various adjustment strategies to forecast development plans, as well as data sensitivity analysis and optimization has been included in this study. In addition, to establish a desirable development plan, the simulation model is set up in great consistency with the geological model resulted from the seismic and logging interpretations. Also, emphases are paid on establishing matches with the reported lab data from production wells by PVTi. Results revealed that the specific reservoir development plan intends to reinstate or maintain formation pressure of the X reservoir. All design and optimization studies are set to comprehend the reservoir with the numerical model.

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“…is study mainly focused on how the spatial characteristics of rock joints (n, α, β, and the cutting positions of LSS) affect the mechanical behavior of the specimen (in terms of σ t , E t , and failure mode). e specimen model was a cylinder that is 50 mm in diameter and 100 mm in height, as suggested by the International Society for Rock Mechanics [33][34][35][36]. All joints were considered to cut through the specimen.…”

Section: Models and Parametersmentioning

confidence: 99%

Numerical Analysis of the Mechanical Behavior and Failure Mode of Jointed Rock under Uniaxial Tensile Loading

Zhao

et al. 2020

Advances in Civil Engineering

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In the field of rock engineering, tensile failure is one of the most significant failure modes due to the presence of joints/fractures. However, due to the limitations of current laboratory testing, it is difficult to carry out direct tensile tests on jointed rock specimens in the laboratory. To study the effect of joints on the mechanical behavior and failure mode of jointed rock specimens, a three-point modeling method that can consider arbitrarily arranged rock joints is deduced and applied to discrete element simulation. The effects of different joint angles (the inclination angle α, rotation angle β, and superimposed angle γ of α and β, where γ is the angle between the joint and horizontal plane), the density (n), and the rate of cutting area (RCA) of the specimen loading surface (LSS) on the tensile strength (σt), elastic modulus in tension (Et), and failure mode of the specimens were analyzed. The results show that the joint angle (considering α, β, and γ) and RCA have a significant effect on the resulting σt and failure mode, while n has a significant effect on Et. The failure mode of the specimen changes from tensile failure along the joint to direct tensile failure of the specimen as γ increases, and the mechanical behavior transitions from unstable to stable. In addition, the main influence of γ on the mechanical behavior of specimens is revealed, and the change process of the failure mode after the cutting of the LSS is analyzed. The present research can be utilized for multiple purposes, including the joint development of surrounding rock and failure dominated by tensile failure in underground engineering, especially for tunnels, roadways, chambers, and so forth.

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A novel type of neural networks for feature engineering of geological data: Case studies of coal and gas hydrate-bearing sediments

Cited by 42 publications

References 74 publications

A 3D FIB‐SEM technique for quantitative characterization of oil shale's microstructure: A case study from the Shahejie Formation in Dongying Depression, China

A 3D FIB‐SEM technique for quantitative characterization of oil shale's microstructure: A case study from the Shahejie Formation in Dongying Depression, China

Simulating the strategies of oil field development for enhanced oil recovery

Numerical Analysis of the Mechanical Behavior and Failure Mode of Jointed Rock under Uniaxial Tensile Loading

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