Robert Will

Characterization of induced seismicity patterns derived from internal structure in event clusters

Seismicity induced by CO2 injection at Decatur, Illinois, occurs in distinct clusters and shows no obvious correlation with the proceeding pressure front. We analyse some of these clusters in more depth by using a waveform cross-correlation approach. With this approach we can associate about 1400 events from two clusters, with moment magnitudes between 1.1 and -1.7, with specific formations of much smaller vertical dimensions (10th of meters) than the depth resolution of traveltime-based event locations. The differentiation of reservoir and basement events, and the definition of sub-clusters by waveform correlation, rather than by location, helps to better analyse the spatio-temporal evolution of the events within a cluster. In the Decatur case, this is characterized by event migration from the reservoir into the adjacent basement. The spatial variation of Brune stress drop and Gutenberg b-value exhibit signs of a fluid-driven triggering mechanism at the cluster level, revealing a punctual hydraulic connection between reservoir and basement, most likely associated with basement faults cutting into the reservoir. The observed clustering of seismicity can thus be explained by the lateral heterogeneity of permeability and crustal strength, and is overall consistent with a pressure-induced triggering mechanism. Hence, proper long-term risk mitigation for large-scale fluid injection close to the basement requires prior mapping of small sub-seismic basement-connected faults.

Simulation model analysis of the most promising geological sequestration formation candidates in the Rocky Mountain region, USA, with focus on uncertainty assessment

The purpose of this report is to report results of reservoir model simulation analyses for forecasting subsurface CO2 storage capacity estimation for the most promising formations in the Rocky Mountain region of the USA. A particular emphasis of this project was to assess uncertainty of the simulation-based forecasts. Results illustrate how local-scale data, including well information, number of wells, and location of wells, affect storage capacity estimates and what degree of well density (number of wells over a fixed area) may be required to estimate capacity within a specified degree of confidence. A major outcome of this work was development of a new workflow of simulation analysis, accommodating the addition of “random pseudo wells” to represent virtual characterization wells.