Development of a New Diagnostic Tool by Wavelet Transform & Applications to Stimulation and Waterflooding Operations

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UNAL-DISSERTATION-2019.pdf (4.86 MB)

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2019-08

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Abstract

Due to the shift from conventional reservoirs towards unconventional, ultra-low permeability reservoirs in the last decade, multistage hydraulic fracturing in horizontal wells and Diagnostic Fracture Injection Test (DFIT) has become one of the dominant and economically practical stimulation techniques and pressure transient tests, respectively. It is crucial to analyze and interpret both fracturing and DFIT data correctly to obtain essential features of the fracture and reservoir in order to have successful stimulation designs. In addition, it is also crucial to understand interwell connectivity (IWC) for improving the performance of any secondary flooding in conventional reservoirs.

This research presents a new diagnostic tool/methodology developed by wavelet transform and its applications to hydraulic fracturing, diagnostic testing in unconventional reservoirs and waterflooding operations in conventional reservoirs. This new diagnostic tool provides a better understanding of fracture behavior during both injection and fall-off periods mainly in hydraulic fracturing operations and fracture diagnostic injection tests, respectively. Furthermore, the flexibility of this methodology allows for implementation to conventional reservoirs to determine interwell connectivity between injection and production wells and thus leading to better diagnostics beyond the wellbore.

The objective of this research is to develop a new technology that is applicable for both conventional and unconventional reservoirs to decrease uncertainty not only in commonly used conventional fracture diagnostic techniques such as G-function, log-log analysis, square-root-time, cross-correlation to identify fracture and reservoir parameters, but also level of connectivity in conventional reservoirs to ultimately improve the overall efficiency of hydraulic fracturing designs and enhanced oil recovery where the assessment of connectivity is critical.

Unlike other conventional techniques, this new methodology treats hydraulic fracturing pressure, DFIT fall-off pressure and injection/production rates as non-stationary signals and extracts relevant key information in wavelet/scale domain instead of time domain.

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Keywords

Wavelet transformation, Hydraulic fractures, Waterflooding, Signal energy, Change point detection

Citation

Portions of this document appear in: Unal, E., F. Siddiqui, and M. Y. Soliman. "Wavelet Analysis of Fracturing Pressure Data." In SPE Hydraulic Fracturing Technology Conference and Exhibition. Society of Petroleum Engineers, 2018. And in: Unal, Ebru, Fahd Siddiqui, Mohamed Y. Soliman, and Birol Dindoruk. "Wavelet Analysis of DFIT Data to Identify Fracture Closure Parameters." In SPE Hydraulic Fracturing Technology Conference and Exhibition. Society of Petroleum Engineers, 2019. And in: Unal, Ebru, Ali Rezaei, Fahd Siddiqui, Fatmir Likrama, M. Soliman, and Birol Dindoruk. "Improved Understanding of Dynamic Fracture Behavior in Unconventional Horizontal Wells Using Wavelet Transformation." In SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers, 2019. And in: Unal, Ebru, Fahd Siddiqui, Ali Rezaei, Ibrahim Eltaleb, Shah Kabir, Mohamed Y. Soliman, and Birol Dindoruk. "Use of Wavelet Transform and Signal Processing Techniques for Inferring Interwell Connectivity in Waterflooding Operations." In SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers, 2019.

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https://hdl.handle.net/10657/5335

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