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Mapping Rock-Property Changes and Fluid Migration During Hydraulic Fracturing Using FWI of Microseismic Data

Abstract

Microseismic data generated during hydraulic fracturing contain a wealth of information, but currently, we are extracting only a small fraction of that information. The primary objectives of this novel microseismic data analysis methodology are threefold -- 1. Accurately image natural and stimulated fractures, 2. Image and distinguish stimulated zones from under- and un-stimulated zones, 3. Provide accurate flow and fracture parameters to be input into reservoir simulation.

Microseismic waves travel through the whole subsurface; therefore, they are sensitive to elevated pore pressures (stimulated and hydraulically connected zones) and elevated confining stress(unstimulated and bypassed zones). Here, we present a novel methodology to accurately map the pressure and stress changes in detail within and around the reservoir using inversion of microseismic data. The methodology reduces the volume of microseismic data and then performs an efficient inversion to yield a 3D high-resolution image of the effective stress changes in the subsurface. Inversion is performed using an advanced algorithm called waveform inversion that generates an optimal map of the subsurface velocity that can accurately predict the microseismic waves passing through it. The same inversion procedure is performed for different stages of hydraulic fracturing to yield a time-lapse image of the reservoir that each stage stimulates.

The presented methodology generates a high-resolution velocity map of the reservoir where the effects of hydraulic fracturing on the reservoir rocks show up as anomalies. The velocity of the stimulated rock volume decreases while the bypassed rocks experience an increase on velocity. The velocity image also provides direct visual evidence of fractures and fluid pathways. All this information plays a critical role in well planning and field development and helps in enhancing the estimated ultimate recovery. Moreover, the inversion can be done for every stage separately, thereby giving a time-lapse picture of changes in the reservoir due to the different fracturing stages. This enables more informed decision making in reservoir stimulation even in real time. In addition, we can analyze the velocity image to determine the fracture opening and tortuosity to be input into the reservoir simulator. Moreover, such an image can provide a more accurate estimate of the stimulated reservoir volume (SRV).

Using the novel methodology presented here, one can use microseismic data to accurately monitor the effect of hydraulic fracturing and extract valuable information about the reservoir. Using this methodology, we can extract valuable information out of microseismic data including accurately defining flow pathways, determine natural and stimulated fracture parameters, and distinguish stimulated zones from bypassed zones, planning optimal re-fracturing operations, etc.