Normalized edge detection, and the horizontal extent and depth of geophysical anomalies

空间归一化边界识别方法用于判断地质体的水平位置及深度(英文)

Edge detection is an image processing technique for finding the boundaries of objects within images. It is typically used to interpret gravity and magnetic data, and find the horizontal boundaries of geological bodies. Large deviations between model and true edges are common because of the interference of depth and errors in computing the derivatives; thus, edge detection methods cannot provide information about the depth of the source. To simultaneously obtain the horizontal extent and depth of geophysical anomalies, we use normalized edge detection filters, which normalize the edge detection function at different depths, and the maxima that correspond to the location of the source. The errors between model and actual edges are minimized as the depth of the source decreases and the normalized edge detection method recognizes the extent of the source based on the maxima, allowing for reliable model results. We demonstrate the applicability of the normalized edge detection filters in defining the horizontal extent and depth using synthetic and actual aeromagnetic data.

边界识别是重磁数据解释中的常用方法之一,依据其结果可划分出地质体的水平范围。边界识别结果受地质体埋深及导数计算误差的影响所识别边界与真实边界之间存在一定的差距,且边界识别法无法直观地给出地质体的深度信息。为了获得异常体的水平位置和深度信息,本文提出空间归一化边界识别方法,其对不同深度的边界识别函数进行归一化计算,空间归一化边界识别法的最大值对应于异常体的水平位置和深度。常规边界识别结果的误差随理深的减小而减小,而空间归一化边界识别法是通过最大值来判断地质体的位置,最大值是在地质体处获得,因此归一化边界识别方法所获得的结果是准确的。通过理论模型试验证明归一化边界识别方法能有效地完成异常体的水平位置和深度的计算,所获得的水平位置和深度信息与理论值相一致,为下一步的勘探计划提供了更加可靠的依据。将其应用于实际航磁数据的解释,获得了断裂的具体分布形式。