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Seismic source and elastic full-waveform inversion using distributed acoustic sensing and perforation shots in unconventional reservoirs

Milad Bader, Stanford University

Month and year defended: October 2023

Unconventional oil and gas resources will maintain a significant presence in the global energy landscape for the foreseeable future. Nevertheless, our comprehension of unconventional reservoirs remains limited and has not fully harnessed advancements in seismic imaging technologies. The introduction of distributed acoustic sensing (DAS) technology has paved the way for various geophysical applications in these reservoirs through fiber optic deployment in horizontal wells. These applications primarily focus on characterizing fractures but fail to provide a holistic characterization of the entire reservoir.

I propose harnessing the cost-effective DAS-recorded seismic waves generated by perforation shots within an elastic full-waveform inversion (FWI) framework. This approach aims to estimate high-resolution elastic properties, which can serve multiple purposes, including mapping heterogeneities, assessing potential hazards, refining reservoir models, and monitoring stimulation and production operations.

This dissertation addresses two principal challenges in pursuit of this goal. First, the representation of perforation shots as seismic sources remains undefined. I develop a source model based on a superposition of three mechanisms and derive the corresponding moment tensor representation. A workflow for estimating source parameters from field DAS data is established, with the moment tensor serving as an indicator of a perforation shot’s effectiveness in creating microcracks. Second, seismic sources within the layer of interest introduce significant footprints in the FWI results. I propose a simple and effective method for footprint removal while robustly updating the model in their vicinity. This method leverages illumination redundancy and extends the model along the sources. Each source updates one component of the extended model, with a regularization term ensuring mutual consistency among these components. After demonstrating the method’s resilience to source-related errors, I apply it to a field DAS data set, successfully identifying meter-scale reservoir anomalies indicative of denser shale regions. I further adapt this method to assess the long-term stimulation effects, revealing only a mild decrease in S-wave speed.

Finally, I extend my investigations to encompass source and elastic parameter estimation in a 3D geometry using crosswell DAS/perforation data. The results highlight the prevalence of explosion and tensile crack mechanisms as dominant source mechanisms and emphasize significant lateral variations in elastic parameters.

Adviser: Biondo Biondi