| dc.description.abstract | Hydraulic fracturing stimulation has become a standard practice to enhance productivity of oil and gas wells in unconventional reservoirs (such as shale, tight sand, coal beds, etc.) previously considered difficult to access. Microseismic (MS) monitoring is routinely used during hydraulic fracturing currently, as a diagnostic technique to assess the created fracture geometry.
Despite the technical and economic successes, hydraulic fracturing suffers two uncertainties. First, hydraulic fracture height prediction by equilibrium-height method, significantly affecting fracture treatment design and other issues, is rarely done rigorously, owing to the complexity of the algebra and the reservoir geology. The secondary, unrealistic solution pairs of height tips exist but are not addressed by previous height models. Second, fracture dimensions and stimulated reservoir volume (SRV) implied by MS events are still controversial, because adjacent fracture stimulation stages of horizontal wells severely overlap each other, thus leading to over estimation of future production. In this work, we addressed the first problem by developing a Multilayer Fracture Equilibrium-Height Model (MFEH); the second problem by extracting shut-in period MS data (Closure Window) to describe effective SRV.
First, we developed the MFEH model that can rigorously calculate the stress intensity factor (SIF) at two fracture tips and solve the equilibrium height problem in multilayer formation, no matter where the perforations are placed. The MFEH model eliminates those unrealistic secondary solutions by seeking the tip solution pair from the positions nearest the initial fracture. In addition, we introduced a rigorous concept of net pressure base to calculate “apparent” net pressure, by setting fracture toughness of initial fracture tip locations to zero and then calculating the minimum treating pressure to grow the initial fracture.
By comparing the MFEH model with previous models, we found the three-layer models are not reliable due to errors in the equations; the modified MW model is correct in the equation to calculate SIF but didn’t address the secondary solution problem; MShale and FracPro have little difference from the MFEH model if layers are normally stressed, although MShale is more reliable than FracPro, but they yield large discrepancy when there are abnormally high or low stress in the adjacent layers of the perforated interval. By studying the tip growth sensitivity to in-situ stress, fracture toughness, and fluid density, we found tip jump is caused by low in-situ stress; tip stability is imposed by large fracture toughness and/or large in-situ stress.
Second, we developed an Excel-VBA program to divide the MS events for each fracture stage into three windows: Pad, Proppant, and Closure Windows. The Closure Window includes only MS events during the shut-in period (from the end of slurry pumping), where leakoff and fracture closing are the dominant phenomena. Then we developed a Mathematica program to calculate SRV volume and area. We applied the Closure Window method to 5 shale wells. The overlap of MS events of stages is reduced in Closure Window. Closure Window shifts apart from other two windows, and shifts away from previous stage. Historic production is better matched with reduced fracture geometry. The SRV area ratio of Closure/Entire window is 0.7, and SRV volume ratio of Closure/Entire window is 0.75.
Finally, to improve fracture treatment design, and predict productivity, we did an integrated study of two Fayetteville fractured horizontal wells using a fracture simulator and a reservoir simulator, integrating geology data, reservoir properties from well logs and well test, perforation and well survey data, fracture pump schedules, and MS monitoring data, as well as parameters from literature. Fracture geometry and production are history-matched. Some preliminary means to improve fracture effectiveness are proposed. | en |
