Addressing Microseismic Uncertainty from Geological Aspects to Improve Accuracy of Estimating Stimulated Reservoir Volumes

Abstract

Abstract Unconventional resources development has had a great success in North America. But this success has not yet been duplicated in every tight oil or tight gas reservoir. A big challenge is how to correctly demonstrate and evaluate hydraulic fracturing outcomes, which are usually estimated by a stimulated reservoir volume (SRV). Microseismic data is a fundamental element to estimate a SRV. However, most microseismic signals are generated by shear fracturing, while hydraulic fracturing can induce tensile fracturing as well, which cannot be well reflected by microseismic data. A long distance between fracturing places and geophones can also make signals unclear and undetectable. Thus a sole microseismic interpretation has its own limitations. Integrating geological information and microseismic data can provide us with a valuable guide to increase the accuracy of an estimated SRV. In this study, detailed geological data and well logs are applied to evaluate rock mechanical properties. As known, under the same hydraulic fracturing treatment conditions, a more brittle rock interval can form more fractures, and a rock interval with more natural fractures can generate more complex fractures. The near-wellbore zones are first evaluated by a rock mechanical index based on how the rock is prone to form hydraulic fractures. A rock mechanical model of a whole shale layer is further determined by a Pixel-Based reservoir modeling method. A rock mechanical index is used as a criterion to address the microseismic data uncertainty. Comparing a rock mechanical model with a SRV, some mismatched areas are located, the microseismic uncertainty is addressed, and the microseismic signal threshold criteria are then adjusted in these areas. As a result, a SRV in the mismatched areas is further modified based on a rock mechanical index value and a different signal dataset. This approach has been applied in the Biyang shale oil reservoir, China. Compared with the successful Barnett marine shale formation, the target shale layer was deposited in a continental lacustrine environment with complex laminations and high heterogeneous rock mineral compositions. Comparing the SRV generated by original microseismic data with the newly SRV generated by applying this approach, the new one can precisely represent hydraulic outcomes and illustrate complex dual-permeability flow for unconventional reservoir development. The proposed approach is a good and valuable guide to increase the accuracy of estimating SRV.