Monitoring of induced microseismic events usually results in locations for these events and a geometrical interpretation of these 'dots in the box'. In this study we show how additional information obtained from observed microseismic events, namely the source mechanisms, were used to generate a discrete fracture network. Using the wide aperture of a surface star-like array (FracStar®) allows inversion for both shear and non-shear source mechanisms. Both volumetric and shear-only source mechanism inversion was carried out on microseismic events from the treatment of a shale gas reservoir in the continental US. During the same hydraulic fracture stimulation treatment, both dip-slip and reverse faulting sources were active in this reservoir. The source mechanisms revealed fracture orientations more accurately than could be inferred from microseismic event locations alone. The activity associated with different mechanisms is interpreted as indicating reactivation of existing fractures in the rock, as well as suggesting generation of new fractures. Failure analysis using source mechanisms on individual events allows an integrated understanding of the complex fracture interactions taking place in the reservoir, and also provides a more complete understanding of the stress conditions in the reservoir during the treatment. Fracture orientations, locations, and failure mechanisms are translated into discrete fracture network (DFN) models that can be used to verify the extent and character of the fractures created or reactivated during the fracture treatment, and may ultimately be used to generate fracture flow properties for reservoir simulation.
The results of monitoring of carbon dioxide (CO2) injection at the Illinois Basin—Decatur Project (IBDP) and the companion Illinois Industrial Carbon Capture and Sequestration Sources (IL-ICCS) project—have shown that reservoir response to fluid pressure changes can vary significantly at different injection locations within the same reservoir. Predrill reservoir characterization is important to identify potentially seismogenic faults. However, interpretations of newly reprocessed 3D seismic reflection data illustrate the challenges related to their identification in a region dominated by faulting with small vertical offsets. Faults interpreted in the 3D seismic volume range from ∼300 to 1200 m wide and are in the same size range as faults that could have been the source of historical events up to Mw 2.7 in central Illinois. The array of monitoring sensors that was installed for the IBDP continues to collect data, as injection operates in IL-ICCS, the second injection well. CO2 injection rates for the IL-ICCS well are on average 1.7 times the rates injected in the IBDP well, but a significantly reduced rate of induced seismicity is observed. This article presents results of passive seismic monitoring for the duration of the project to date, integrating active and passive seismic data to develop a new interpretation of the subsurface structure at the Decatur site that explicitly identifies pathways for fluid flow into the basement leading to induced seismicity, and provides a geological explanation for the sharp reduction of induced seismicity during injection at higher rates into the second well. The use of seismic moment to estimate the length of seismogenic slip planes in the local subsurface suggests that faults large enough to produce felt seismicity are unlikely to be present at or near the Decatur site.
The effectiveness of hydraulic fracture stimulation in low-permeability reservoirs was evaluated by mapping microseismic events related to rock fracturing. The geometry of stage by stage event point sets were used to infer fracture orientation, particularly in the case where events line up along an azimuth, or have a planar distribution in three dimensions. Locations of microseismic events may have a higher degree of uncertainty when there is a low signal-to-noise ratio (either due to low magnitude or to propagation effects). Low signal-to-noise events are not as accurately located in the reservoir, or may fall below the detectability limit, so that the extent of fracture stimulated reservoir may be underestimated. In the Bakken Formation of the Williston Basin, we combined geologic analysis with process-based and stochastic fracture modeling to build multiple possible discrete fracture network (DFN) model realizations. We then integrated the geologic model with production data and numerical simulation to evaluate the impact on estimated ultimate recovery (EUR). We tested assumptions used to create the DFN model to determine their impact on dynamic calibration of the simulation model, and their impact on predictions of EUR. Comparison of simulation results, using fracture flow properties generated from two different calibrated DFN scenarios, showed a 16% difference in amount of oil ultimately produced from the well. The amount of produced water was strongly impacted by the geometry of the DFN model. The character of the DFN significantly impacts the relative amounts of fluids produced. Monitoring water cut with production can validate the appropriate DFN scenario, and provide critical information for the optimal method for well production. The results indicated that simulation of enhanced permeability using induced microseismicity to constrain a fracture flow property model is an effective way to evaluate the performance of reservoirs stimulated by hydraulic fracture treatments.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.