A fractally fractional diffusion model of composite dual-porosity for multiple fractured horizontal wells with stimulated reservoir volume in tight gas reservoirs

Journal Article (2019)
Author(s)

Daihong Gu (China University of Petroleum - Beijing)

Daoquan Ding (PetroChina Southwest Oil and Gas Field Company)

Zeli Gao (PetroChina Southwest Oil and Gas Field Company)

Leng Tian (China University of Petroleum - Beijing)

Lu Liu (PetroChina Dagang Oilfield Company)

C. Xiao (TU Delft - Mathematical Physics)

Research Group
Mathematical Physics
DOI related publication
https://doi.org/10.1016/j.petrol.2018.10.011
More Info
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Publication Year
2019
Language
English
Research Group
Mathematical Physics
Volume number
173
Pages (from-to)
53-68

Abstract

Based on fractal theory (FT) and fractional calculus (FC), a new fractally fractional diffusion model (FFDM) of composite dual-porosity has been developed to evaluate performance of multiple fractured horizontal wells (MFHWs) with stimulated reservoir volume (SRV) in tight gas reservoirs (TGRs). More specifically, FT is used to characterize the complex and heterogeneous fracture network (FN) both inside and outside of SRV, while anomalous behavior of diffusion processes both inside and outside of SRV is quantified by applying the temporal fractional derivatives. The FFDM is then solved by the Laplace transformation, line source function, the numerical discrete method, and superposition principle. The transient pressure responses are then inversely converted from Laplace domain into real time domain with the Stehfest algorithm, and the FFDM is also validated, and type curves are generated as well. Flow stages are subsequently identified together with analysis on characteristics of the type curves, especially the anomalous features different with those generated from the conventional Euclidean model. Sensitivity analyses of some related parameters have also been discussed as well. And the FFDM is then also matched with the real field well-testing data of a MFHW with SRV in a TGR. The proposed FFDM provides a new understanding of the performance of MFHWs with SRV in TGRs, which can be used to interpret the field pressure data more accurately and appropriately.

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