Probabilistic body wave tomography in a geothermal setting in Cornwall

Geothermal systems provide a low-carbon, renewable source of heat, whose performance depends on the presence of permeable, fluid-filled rock at depth. Tomographic images of compressional and shear-wave velocities, Vp and Vs, and their ratio, Vp/Vs, are typically used to constrain the lithology, porosity, fluid content and extent of fracturing in such systems: contrasts in seismic velocity delineate lithological boundaries, identify zones of fracture damage or fluid saturation, and thereby indicate areas of elevated permeability.

Passive seismic acquisition is attractive for geothermal exploration, because it is minimally invasive and can exploit microseismicity recorded by dense nodal seismological arrays. Combining data recorded from microseismic events with Bayesian joint inversion of seismic velocity and source location – here implemented with stochastic Stein Variational Gradient Descent (sSVGD) and double difference tomography – yields relocated earthquake events and three-dimensional estimates of Vp, Vs, and Vp/Vs together with their respective uncertainty. sSVGD approximates the statistical description of all possible models that fit the data, referred to as the posterior distribution, using an ensemble of particles or samples. These are initialized from a prior distribution, which encodes the prior information about the domain, and driven toward the posterior by iterative transforms that minimise the Kullback-Leibler divergence between the particle density and the posterior.

We apply this workflow to the Eden Project geothermal site (Cornwall, UK), using microseismic events recorded by an array of 450 STRYDE nodes deployed around the injection site. The objective is to recover mean models of Vp and Vs, and Vp/Vs with their corresponding uncertainty from passive sources alone, enabling probabilistic assessment of the subsurface structure and potential future well-placement targets.

Owing to the nodal geometry and the spatial distribution of microseismic sources, ray-path coverage is highly heterogeneous across the survey volume. Consequently, the posterior uncertainty is large over much of the domain and decreases substantially where ray coverage is dense – mostly around the geothermal well. Within this region, we observe velocity anomalies consistent with fractured and fluid-saturated rock, while regions distant from the well remain poorly constrained. By providing a clearer understanding of uncertainties inherent to tomographic inversions, the probabilistic imaging framework enables more robust and reliable analysis of the results, which is crucial in geothermal exploration.