Accurate characterization of full pore size distribution of tight sandstones by low‐temperature nitrogen gas adsorption and high‐pressure mercury intrusion combination method

Abstract

The full pore size distribution represents the integrated characteristics of micro‐nano pore‐throat systems in tight reservoirs. And it involves experiments of different scales to fully analyze the microscope properties. In this paper, we established a new approach for full pore size characterization through conducting the high‐pressure mercury intrusion (HPMI) experiments and low‐temperature nitrogen gas adsorption (LTN2GA) experiments. Meanwhile, we studied the petrology feature of the tight sandstones through X‐ray diffraction (X‐rD) and TESCAN Integrated Mineral Analyzer (TIMA). Then, we investigated the HPMI capillary pressure curves and pore size distribution characteristics, as well as the adsorption‐desorption isotherms features and BET‐specific surface area. Finally, the BJH, non‐local density functional theory (NLDFT) and the quenched solid density functional theory (QSDFT) are contrasted for analyzing the adsorption and pore size distribution characteristics. The HPMI method characterizes the macropores distribution accurately, and the micro/mesopores take up of 14.47% of the total pore spaces. The physisorption isotherms take on the combining shape of type II and IV(a), and the hysteresis loops are like type H3 combined with H4. The BET‐specific surface area is inversely proportional to permeability, and the constant of adsorption heat shows consistence with the analysis results of mineral content. QSDFT can characterize the pore size distribution of micro/mesopores more accurately than the BJH, HPMI, and NLDFT method. By combining the pores narrower than 34 nm calculated from QSDFT method and pores larger than 34 nm calculated from HPMI data with mercury intrusion pressure lower than 42.65 MPa, the full pore size distribution features of tight sandstones are accurately characterized. The micro/mesopores from the new combination method are 3.72% more than that calculated from the HPMI data, and it is of great significance for the accurate pore distribution evaluation and development of tight reservoirs.

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