Joint Self‐Potential and Fluid Flow Inversion for Imaging Permeability Structure and Detecting Fractures

ABSTRACT Accurately detecting the locations of fractures and the permeability structure within a subsurface reservoir can significantly improve the optimization of production performance. Achieving peak performance in subsurface groundwater or hydrocarbon reservoirs depends on creating an accurate map that details the reservoir's characteristics derived from the history‐matching process. However, this process involves repeated forward modelling simulations until the results align with historical production data, often consuming significant resources and potentially yielding non‐unique reservoir models. An integration approach between bottom‐hole pressure data and surface self‐potential measurements was used to perform simultaneous inversion for the permeability structure. The self‐potential method, a cost‐effective geophysical technique, allows for the inversion of subsurface self‐potential sources based on the underlying resistivity structure. Through a series of synthetic experiments, we demonstrate that combining borehole pressure data with surface self‐potential measurements significantly enhances reservoir characterization, providing more robust and accurate subsurface models. By using the resolution matrix, we further confirm that the solution achieves higher accuracy when both data sets are integrated. This approach not only improves the precision of reservoir mapping but also reduces the uncertainty typically associated with traditional methods, offering a more efficient and reliable tool for optimizing production performance.