Detection of the oil–water encroachment front is of great importance to water injection of oil reservoirs. In borehole-to-surface electrical imaging (BSEI), a high-power direct current is applied into a borehole through a well case and the electric potential on the surface, which is affected by the subsurface electrical change, is measured. However, further accurate interpretation of BSEI data is difficult due to the weak surface response, deep target layer, long inversion time, and uncertainty in unconstrained inversion. Therefore, a new method to enhance the surface response of the anomalous body and a new three-dimensional inversion approach based on the damped least-squares method are proposed. Simulation of the water injection and fracturing process was modeled in three dimensions using the finite difference method and the incomplete Cholesky conjugate gradient method. The inversion approach was applied by using the log data to construct a layered resistivity model and constrain the inversion. The forward modeling results suggest that the electric potential gradient can enhance the response of electrical variations in the target layer and help estimate the water injection direction, depending on the distance of electrical anomalies and the current source. In actual water injection monitoring, the BSEI inversion results suggest that layered resistivity model constrained three-dimensional inversion can improve the precision and accuracy of the resistivity inversion results and outline the water injection channeled to the adjacent wells.

检测油水侵入前沿对储油层注水非常重要。在井下地表电成像（BSEI）中，将高功率直流电通过井筒施加到井眼中，并测量受地下电变化影响的地表电位。但是，由于表面响应弱，目标层深，反演时间长以及反演的不确定性，很难进一步准确解释BSEI数据。因此，提出了一种增强异常物体表面响应的新方法以及一种基于阻尼最小二乘法的三维反演方法。使用有限差分法和不完整的Cholesky共轭梯度法在三个维度上对注水和压裂过程进行了模拟。通过使用测井数据来应用反演方法来构建分层电阻率模型并约束反演。前向建模结果表明，电势梯度可以增强目标层中电学变化的响应，并根据电异常的距离和电流源来帮助估计注水方向。在实际注水监测中，BSEI反演结果表明，分层电阻率模型约束三维反演可以提高电阻率反演结果的精度和准确性，并勾勒出注入相邻井的注水轮廓。