2022
DOI: 10.1155/2022/2729597
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Coupling Relationship between Lithofacies and Brittleness of the Shale Oil Reservoir: A Case Study of the Shahejie Formation in the Raoyang Sag

Abstract: Analyzing the characteristics of rock brittleness in low-permeability mudstone and shale (MS) formations is imperative for efficient hydraulic fracturing stimulation. Rock brittleness depends on the mineral composition, organic matter abundance, and bedding structure. Based on the MS from Shahejie Formation mineral composition (clay mineral, felsic mineral, and calcareous mineral contents), total organic content, and bedding structure (laminated, laminar, and massive), six types of lithofacies were identified:… Show more

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Cited by 8 publications
(3 citation statements)
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“…However, with the rapid development of the global shale oil and gas industries, shale and mudstone lithofacies analysis is increasingly valued [18][19][20]. Therefore, as an important target of unconventional oil and gas, there developed a series of machine learning methods to predict the identification and classification of shales and mudstones lithofacies [21][22][23].…”
Section: Introductionmentioning
confidence: 99%
“…However, with the rapid development of the global shale oil and gas industries, shale and mudstone lithofacies analysis is increasingly valued [18][19][20]. Therefore, as an important target of unconventional oil and gas, there developed a series of machine learning methods to predict the identification and classification of shales and mudstones lithofacies [21][22][23].…”
Section: Introductionmentioning
confidence: 99%
“…Feldspar is a brittle mineral 62 with strong compressive resistance, and the pores between particles are easily preserved during the burial process. Feldspar particle crystals are relatively regular, with mostly triangular, quadrilateral, or polygonal pores; these spaces are primarily classified as P mes (Figure 4c).…”
Section: Feldsparmentioning
confidence: 99%
“…Shale Oil Enrichment Model. Song et al used a BP (Back Propagation)neural network combined with X-ray diffraction (XRD) to predict the mineral components of 61 wells in the study area,76 got XiLiu3 -Liu490 lithofacies section (Figure15), corresponding to the section line in Figure1. Considering the microscopic characteristics and depositional environment, the shale oil enrichment model of the Raoyang sag has been established.…”
mentioning
confidence: 99%