Experimental investigation and theoretical modeling of stress-dependent permeability in naturally fractured tight gas reservoir

Abstract

Stress-dependent permeability (SDP) of naturally fractured tight gas reservoir (NFTGR) has drawn considerable attention in recent decades. The SDP of natural fracture (NF) is quite different from that of the rock matrix (RM) due to the variance NF width and NF filling degree. The SDP of naturally fractures can be obtained by conducting permeability measurement experiments on naturally fractured core plugs (NFCP). However, it is usually impossible to obtain downhole NFCPs due to economic and technical limitations. Our research group obtained various types of naturally fractured downhole core plugs from a NFTGR (Tarim filed, China) and make it possible to investigate the effect of NFs on SDP. The NF types of the downhole core plugs include RM core plug (RMCP), unpenetrated-ring fractured core plug (URFCP), penetrated-vertical fractured core plug (PVFCP), penetrated-incline fractured core plug (PIFCP), unpenetrated-U-type fractured core plug (UUFCP), and multiple fractured core plug (MFCP). We conducted SDP experiments through the application of pressure-pulse-decay (PPD) method. Results showed that the initial permeability of RMCP and MFCP were higher than that of others, and the permeability vanished stress of them were also highest, indicating that the flow resistance of RMCP and MFCP were lower than those of others. It is also shown that the degree of permeability stress-dependent (DPSD) varied from NF types. A modified exponential permeability model was derived to evaluate DPSD of natural fractured core plugs. Two parameters (γσeff and γσeff') were used to describe the DSDP in NFTGR, and the range of which were obtained from the experimental data by regression analysis. The reasonable γσeff and γσeff' range of NFCP were also proposed in this paper. Sensitivity analysis showed that the influence γσeff' on SDP was more significant than that of γσeff. The proposed model can be integrated to reservoir simulators and help to improve of oil and gas production prediction accuracy in NFTGRs.