Abstract
Shale-gas sweet-spot evaluation as a critical part of shale-gas exploration and development has always been the focus of experts and scholars in the unconventional oil and gas field. After comprehensively considering geological, engineering, and economic factors affecting the evaluation of shale-gas sweet spots, a dynamic uncertainty causality graph (DUCG) is applied for the first time to shale-gas sweet-spot evaluation. A graphical modeling scheme is presented to reduce the difficulty in model construction. The evaluation model is based on expert knowledge and does not depend on data. Through rigorous and efficient reasoning, it guarantees exact and efficient diagnostic reasoning in the case of incomplete information. Multiple conditional events and weighted graphs are proposed for specific problems in shale-gas sweet-spot evaluation, which is an extension of the DUCG that defines only one conditional event for different weighted function events and relies only on the experience of a single expert. These solutions make the reasoning process and results more objective, credible, and interpretable. The model is verified with both complete data and incomplete data. The results show that compared with other methods, this methodology achieves encouraging diagnostic accuracy and effectiveness. This study provides a promising auxiliary tool for shale-gas sweet spot evaluation.
Highlights
Shale gas, as an unconventional green energy source in the petroleum industry, has received increasing attention since 2005
The main research focus is combining the achievements and experience of experts and scholars; using the evaluation results of different areas to divide them into target areas, favorable areas, and sweet spots to reduce the risks related to shale-gas exploration and development; and obtaining economic benefits from oilfields [1,2,3]
This paper proposed a weighted-graph method to solve the above problems: X12 has three states in Table 3; for each state, the evaluation model was different
Summary
As an unconventional green energy source in the petroleum industry, has received increasing attention since 2005. Owing to the current environmental problems and resource-intensive energy development, effectively developing China’s shale-gas resources on a large scale is an urgent task of substantial research value and significance. Domestic shale-gas exploration and development is rapidly growing. The main research focus is combining the achievements and experience of experts and scholars; using the evaluation results of different areas to divide them into target areas, favorable areas, and sweet spots to reduce the risks related to shale-gas exploration and development; and obtaining economic benefits from oilfields [1,2,3]. There are many evaluation methods for the exploration and development of various types of oil and gas reservoirs. Jiang proposed the sequential fully implicit (SFI) scheme for solving coupled flow and transport problems [6]
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