A fast and efficient technique for explanation of self-potential anomalies is of immense importance for exploration, engineering, and environmental problems. Estimation of model parameters of ore bodies in the subsurface is the primary concern in mineral exploration. In most cases, self-potential data are delineated considering various simple or idealized structures for the interpretation of lateral and vertical variations of subsurface ore bodies. In this context, we developed an inversion algorithm to determine the different parameters associated with a 2D inclined plate-type structure, which does not require any a priori information. The developed algorithm can interpret appropriately every parameter with minimum uncertainty. The position of causative source body (x₀), its half-width (w) and its depth (z) were the parameters interpreted using the developed algorithm. It was found that these parameters were well resolved within the estimated uncertainty, although solutions for w showed wide variability. The technique was verified with synthetic data without noise and with different degrees of Gaussian noise. The technique was also confirmed with three field datasets for mineral exploration, and the interpreted parameters were in fair agreement with those reported in earlier works.

快速有效的技术来解释自潜异常对勘探，工程和环境问题具有极其重要的意义。地下矿体模型参数的估计是矿物勘探的主要关注点。在大多数情况下，考虑各种简单的或理想的结构来描述地下矿体的横向和纵向变化，从而描绘出自势数据。在这种情况下，我们开发了一种反演算法来确定与2D倾斜板式结构相关的不同参数，该参数不需要任何先验信息。所开发的算法可以以最小的不确定性适当地解释每个参数。原因源体（x ₀）的位置，其半角（w）及其深度（z）是使用开发的算法解释的参数。已发现，尽管w的解显示出很大的可变性，但这些参数在估计的不确定性内得到了很好的解析。该技术已通过无噪声且具有不同高斯噪声程度的合成数据进行了验证。该技术还得到了三个用于矿产勘探的现场数据集的证实，其解释的参数与早期工作中报道的参数完全一致。