Microseismic monitoring has proven to be an important tool for understanding and optimizing hydraulic fracturing, well completions, and field development in unconventional reservoirs. The microseismic distributions can be used as a proxy to estimate fracture length, azimuth, height, asymmetry, overall complexity, and general stage behavior. However, this technology has a number of limitations for fully understanding the behavior of the hydraulic fracture because it is unclear as to the direct relationship between the microseismic source and the tensile hydraulic fracturing process itself. The integration of other diagnostic technologies with microseismicity is needed to extract more detailed information about the fracturing process, the completion scheme, staging, and other relevant development details. In particular, surface tiltmeters, downhole tiltmeters embedded in microseismic arrays, distributed temperature sensing (DTS), distributed acoustic sensing (DAS), and more conventional diagnostics are used to enhance the understanding of the microseismicity in field applications. A combination of field data, theoretical analyses, and simulations demonstrate how such information can be extremely valuable in optimizing stimulations. The application of these technologies is geared toward unconventional reservoirs where multistage hydraulic fracturing in horizontal wells is the preferred development approach, although application in vertical wells is also useful. These additional technologies are shown to be helpful in evaluating complexity, fracture height growth, staging, cluster effectiveness, and horizontal fracturing in some of the highly tectonic areas, monitoring diversion, assessing isolation, and many other factors in a wide variety of field development cases.
Integrating Fracture Diagnostics for Improved Microseismic Interpretation and Stimulation Modeling
Warpinski, N.R., Mayerhofer, M.J., Davis, E.J., and E.H. Holley. "Integrating Fracture Diagnostics for Improved Microseismic Interpretation and Stimulation Modeling." Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, Denver, Colorado, USA, August 2014. doi: https://doi.org/10.15530/URTEC-2014-1917906
Download citation file: