A probabilistic assessment of induced seismicity and fluid flow in the Carboniferous Limestone of northwest England: Implications for geothermal energy

Faults slip in response to changes in stress or fluid pressure, and these changes can be natural or anthropogenic. Estimating the likelihood of fault slip for a given change in loading is critical for safe geological storage and energy extraction in faulted rocks, as well as effective communication of risks to policy makers and the public. The energy transition and decarbonization are urgent and essential tasks: we will only be successful if we manage to balance public perceptions of risk with the technical challenges inherent to the exploitation of faulted rock. To accomplish both, we need to do a better job of quantifying the uncertainties in our mechanical and geometrical data. 

Measures of fault stability include slip (T_s) and dilation (T_d) tendency, and fracture susceptibility (S_f, the change in fluid pressure to push effective stress to failure). The input values for any of these measures are always uncertain, and they are uncertain to varying degrees. For example, while the vertical stress can be well constrained from wireline density log data, the maximum horizontal stress is generally much harder to quantify from any source.

Probabilistic models of fault stability for the Mississippian (Lower Carboniferous) Limestone underlying much of northern England are presented. This is an undrilled target for geothermal energy. Fault maps are derived from published geological maps and recently reprocessed seismic reflection data. Stress and pressure constraints are derived from legacy onshore hydrocarbon wells and wireline logs. Coefficients of friction and cohesive strength remain poorly constrained, not only in terms of their magnitude, but critically in the shapes of their statistical distributions. In addition, the applicability of simplified indices of fault stability (T_s, T_d, S_f) to complex natural fault zones is questionable, and our predictions could be improved through weighting by information derived from long-term seismological records.  

This contribution raises two key points: 1) Laboratory data rarely include repeat measurements from quasi-identical samples of the same rock, and therefore the statistical distributions of friction or cohesion are poorly known. This is important because skewed distributions – and the direction of that skewness (high or low) – can significantly affect predictions of fault stability; 2) What is the best way to weight the calculated probability of slip in complex natural fault zones to account for geometrical weakening? Specifically, is total fault length more or less important than fault smoothness (roughness)?