Читать книгу Geophysical Monitoring for Geologic Carbon Storage - Группа авторов - Страница 59

The injection of CO₂ into subsurface reservoirs during geological carbon storage changes the stress state of the subsurface through volume and/or mass change, and reduces the effective normal stress by increasing the pore pressure (Ellsworth, 2013). Such changes in stress can induce sudden slip on fractures or faults under certain conditions, generating microseismic events near the target CO₂ storage regions. Induced microseismicity associated with the injection of CO₂ may cause possible leakage of CO₂ or brine from reservoirs along faults, leading to contamination of shallow aquifers. Relatively large induced seismic events may also create public concerns. Microseismic monitoring can play a crucial role to ensure safe long‐term geological carbon storage. Monitoring of induced microseismicity during and after injection operations can help map the movement of CO₂, understand the stress changes in the reservoir, and identify faults and possible leakage pathways (e.g., Maxwell & Urbancic, 2001; Miyazawa et al., 2008; Verdon et al., 2010).

A current microseismic monitoring network includes borehole geophones and surface seismic arrays (e.g., Boullenger et al., 2015; Kaven et al., 2015; Stork et al., 2018). Borehole geophones are more sensitive to small seismic events and surface seismic arrays have better area coverage. The accuracy of microseismic event location depends on the distribution of seismic stations, and thus the optimal design of a seismic network is of great interest to geophysical monitoring. Many previous works on optimal design of a seismic network studied the optimal distribution of seismic stations given a fixed number of total stations using a statistical theory (e.g., Kijko, 1977a,b; Rabinowitz & Steinberg, 1990; Steinberg et al., 1995). Such optimal distribution of surface seismic stations is not necessarily feasible for carbon storage sites considering the permit and geological constraints. In the interest of flexibility and easy adoption by operators, we would like to avoid complicated statistical theory and develop a simple method to study the optimal number of seismic stations for a given geometrically satisfactory network distribution. In other words, we would like to design the seismic network following guidelines based on possible locations of seismic events. Then, we determine the best trade‐off between the event location accuracy and the total number of seismic stations to achieve cost‐effective microseismic monitoring.

The guidelines we follow to design the seismic network distribution are some widely accepted guiding principles based on practical experience and have been provided theoretical basis by some studies (e.g., Chatelain et al., 1980; Kissling, 1988; Gomberg et al., 1990; Rabinowitz & Steinberg, 1990; Husen et al., 2003). Based on these rules, an epicenter can be best located when stations surround it with good azimuthal coverage. A range of station distances is desirable, and the existence of at least one station with small epicentral distance, preferably within about one focal depth, is especially useful for depth determination. The inclusion of S‐wave arrival times besides P‐wave arrival times can improve the hypocenter determination, particularly the depth.

The U.S. Department of Energy (DOE) established the National Risk Assessment Partnership (NRAP) project to develop quantitative risk assessment methodologies for carbon capture, utilization, and storage (CCUS). As part of this initiative, the Kimberlina site in California was proposed as a potential demonstration site. We use the Kimberlina model to demonstrate the application of our optimal design of both surface seismic network and borehole geophone array for microseismic monitoring.