A diagnostic model for hydraulic fracture in naturally fractured reservoir utilising water-hammer signal

Author:

Deng Shijie1,Yi Liangping1,Li Xiaogang1,Yang Zhaozhong1,Zhang Nanqiao2

Affiliation:

1. Southwest Petroleum University

2. Sichuan Shale Gas Exploration and Development Co. Ltd

Abstract

Abstract Diagnostic technique for hydraulic fracture based on the water-hammer pressure have been gradually highlighted owing to their cost effectiveness and simplicity. The present diagnostic models overlook the effects of fluid leak-off and natural fracture, and it is limited in naturally fractured reservoir. In this study, the location and number of hydraulic fractures are first obtained through the enhancement and cepstrum processing of a water-hammer signal. Subsequently, the water-hammer pressure within the wellbore is calculated by solving the continuity and momentum equations for the fluid. Wellbore and hydraulic fractures are considered as a hydraulic system. To estimate the fracture dimension, flow boundary conditions are imposed to the fluid leak-off, interactions between natural and hydraulic fractures, and multifracture stress shadows. Based on the results, (1) the fracturing shut-in method can be appropriately adjusted to avoid large pressure pulsations, which damage well integrity, and to obtain a clear water-hammer signal for fracture diagnosis. (2) As the perforation cluster spacing increases, the fractures on both sides first decrease and then increase, whereas the centre fracture increases consistently. (3) Natural fractures reduce the hydraulic fracture dimensions but facilitate the creation of complex fracture networks; however, this complexity cannot be increased indefinitely. (4) The minimum horizontal stress decreases the fracture dimension and a greater difference in the horizontal stress renders it easier for hydraulic fractures to cross natural fractures to create larger dimensions. (5) The field study demonstrates the practicality of our model, and optimisation measures can be recommended based on the diagnostic results.

Publisher

Research Square Platform LLC

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