Microscopic Pore Structure and Seepage Behavior of Deep Shale Reservoirs Based on Three-Dimensional Digital Cores

Abstract Deep tight shale reservoirs exhibit highly heterogeneous pore structures, resulting in complex flow behavior and restricted hydrocarbon recovery. Understanding seepage characteristics under different pore-structure conditions is therefore essential for improving oil production. In this study, X-ray diffraction, scanning electron microscopy, and computed tomography, combined with 3D digital reconstruction, were used to construct microscale digital cores and characterize shale pore structures qualitatively and quantitatively. Based on these digital cores, hydraulic-mechanical coupled flow simulations were performed to investigate microscopic seepage behavior under different pore-structure conditions. The results show that the shale pore system is highly complex, with a wide pore-size distribution and generally poor connectivity. The average axial porosity of the digital cores is about 3%. Pores smaller than 20 μm account for nearly 90% of the total pore count but only about 10% of the pore volume, and most are closed or isolated; thus, effective flow pathways are mainly provided by a limited number of larger pores and fractures. Flow simulations show that average fluid velocity increases with porosity; however, seepage behavior is governed primarily by the connectivity and configuration of the pore–fracture network. When no through-going sheetlike fractures are present, the peak velocity in the main flow channels is <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="less than 7 times 10 Superscript negative 3 Baseline normal m divided by normal s" display="inline" overflow="scroll"> <mml:mo>&lt;</mml:mo> <mml:mn>7</mml:mn> <mml:mo>×</mml:mo> <mml:msup> <mml:mrow> <mml:mn>10</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>3</mml:mn> </mml:mrow> </mml:msup> <mml:mtext> </mml:mtext> <mml:mi mathvariant="normal">m</mml:mi> <mml:mo stretchy="false">/</mml:mo> <mml:mi mathvariant="normal">s</mml:mi> </mml:math> , whereas through-going fractures approximately parallel to the pressure gradient increase the peak velocity to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="3 times 10 Superscript negative 2 Baseline en dash 7 times 10 Superscript negative 2 Baseline normal m divided by normal s" display="inline" overflow="scroll"> <mml:mn>3</mml:mn> <mml:mo>×</mml:mo> <mml:msup> <mml:mrow> <mml:mn>10</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>2</mml:mn> </mml:mrow> </mml:msup> <mml:mi>–</mml:mi> <mml:mn>7</mml:mn> <mml:mo>×</mml:mo> <mml:msup> <mml:mrow> <mml:mn>10</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>2</mml:mn> </mml:mrow> </mml:msup> <mml:mtext> </mml:mtext> <mml:mi mathvariant="normal">m</mml:mi> <mml:mo stretchy="false">/</mml:mo> <mml:mi mathvariant="normal">s</mml:mi> </mml:math> . Fractal dimension is positively correlated with porosity, whereas mean tortuosity shows only a weak correlation. Permeability is sensitive to porosity but exhibits noticeable scatter, reflecting the additional control of pore connectivity and fracture configuration.