Estimating Pressure and Fronts in Underground Storage Through Tilt Data Inverse Modelling

Seismicity and surface deformation are prevalent outcomes of underground reservoir operations. These deformation data serve as a crucial indirect method into the nature and intensity of subsurface activities. Currently, tiltmeter technology is the most accurate monitoring tools with the accuracy of nano radian. This study aims to utilize surface tilt data acquired from underground storage or production sites to estimate reservoir pressure values and their spatial fronts. To accomplish this, a predictive model was designed to compute surface deformation through numerical methodologies. The model segments the reservoir into smaller elements resembling those used in reservoir simulations. It calculates the resulting deformation caused by pressure alterations by aggregating the results from each individual block under constant pressure conditions. The solution for each block, relies on employing the displacement solution for a thermoelastic strain nucleus within a half-space having a traction-free surface. Integrating a reliable inversion technique with this forward model enables the tracking of pressure fronts in subsurface reservoirs using surface tiltmeter data. The model's proficiency was validated through the utilization of synthetic deformations, highlighting the reliable efficiency of the inversion approach with results demonstrating an error rate below 5%. 1. INTRODUCTION Surface deformation and reservoir compaction have been recorded in a variety of oil and gas fields and storage facilities, stemming from subsurface activities such as fluid extraction or injection, hydraulic fracturing, and fault slippage. (Chen et al., 2023; Du & Olson, 2001; Okada, 1992; Olson et al., 1997). The deformation resulting from subsurface activities or operations can lead to various geo-mechanical challenges, including casing/cement failure, fault reactivation, fracture extension, and surface/subsurface facility failures, as well as caprock failure. This poses a potential risk to the overall well and reservoir integrity. Therefore, monitoring and analyzing deformation data becomes crucial for detecting potential issues. Additionally, these data serve as indirect optimization tools, providing valuable insights into the size and intensity of underground operations or activities, thereby functioning as an indirect monitoring technique for optimizing overall operations.