- Lambert, Valère R;
- Erickson, Brittany A;
- Jiang, Junle;
- Dunham, Eric M;
- Kim, Taeho;
- Ampuero, Jean‐Paul;
- Ando, Ryosuke;
- Cappa, Frédéric;
- Dublanchet, Pierre;
- Elbanna, Ahmed;
- Fialko, Yuri;
- Gabriel, Alice‐Agnes;
- Lapusta, Nadia;
- Li, Meng;
- Marcum, Jasper;
- May, David;
- Mia, Shumon;
- Ozawa, So;
- Pranger, Casper;
- Romanet, Pierre;
- Scuderi, Marco M;
- van Dinther, Ylona;
- Yang, Yuyun;
- Yun, Jeena
Abstract:
Numerical simulations of Sequences of Earthquakes and Aseismic Slip (SEAS) have rapidly progressed to address fundamental problems in fault mechanics and provide self‐consistent, physics‐based frameworks to interpret and predict geophysical observations across spatial and temporal scales. To advance SEAS simulations with rigor and reproducibility, we pursue community efforts to verify numerical codes in an expanding suite of benchmarks. Here we present code comparison results from a new set of quasi‐dynamic benchmark problems BP6‐QD‐A/S/C that consider an aseismic slip transient induced by changes in pore fluid pressure consistent with fluid injection and diffusion in fault models with different treatments of fault friction. Ten modeling groups participated in problems BP6‐QD‐A and BP6‐QD‐S considering rate‐and‐state fault models using the aging (‐A) and slip (‐S) law formulations for frictional state evolution, respectively, allowing us to better understand how various computational factors across codes affect the simulated evolution of pore pressure and aseismic slip. Comparisons of problems using the aging versus slip law, and a constant friction coefficient (‐C), illustrate how aseismic slip models can differ in the timing and amount of slip achieved with different treatments of fault friction given the same perturbations in pore fluid pressure. We achieve excellent quantitative agreement across participating codes, with further agreement attained by ensuring sufficiently fine time‐stepping and consistent treatment of boundary conditions. Our benchmark efforts offer a community‐based example to reveal sensitivities of numerical modeling results, which is essential for advancing multi‐physics SEAS models to better understand and construct reliable predictive models of fault dynamics.