改进的蚂蚁追踪裂缝检测算法及其应用研究

常规蚂蚁追踪裂缝检测技术对小尺度裂缝的识别精度不高，提高蚂蚁追踪技术对裂缝的识别精度很有必要。该文提出一种改进的蚂蚁追踪裂缝检测技术，以地震相干体作为蚂蚁追踪的数据体，以相干值和边缘检测值的线性加权作为启发因子，在信息素和启发因子中选择启发因子作为蚂蚁追踪的主导因素。利用改进的蚂蚁体裂缝检测算法对哈萨克斯坦楚-萨雷苏盆地NH区块致密碳酸盐岩储层进行裂缝检测，结果表明该方法在致密碳酸盐岩储层中能够有效描述小尺度裂缝，与相干、边缘检测、常规蚂蚁追踪等多种技术相比，改进的蚂蚁追踪裂缝检测技术对于构造成因的小断层及裂缝发育带有着极好的识别能力，将断裂刻画得更为精细，反映的裂缝信息更为准确，与新钻井对应层段的成像测井资料相符。

Improved Ant Tracking Crack Detection Algorithm and Its Application

Fracture detection technology based on conventional ant tracing technology is not capable of identifying small scale of fractures. It is necessary to improve the accuracy of ant tracing techniques. In this paper, we propose an improved ant-tracing crack detection technique which uses seismic coherence body as the data body of ant tracing and applies the linear weight of coherence and edge detection as the heuristic factor. Consequently, the heuristic factor is chosen as the dominant factor by comparing with pheromones. Based on the improved ant body crack detection algorithm, the crack detection of the NH block tight carbonate reservoir in the Chu-Sarysu Basin of Kazakhstan was conducted. The results show that this method can effectively describe the small scale of fractures. Compared with many other techniques such as coherence, edg detection and conventional ant tracing, the improved ant-tracing crack detection technology has very good recognition ability for small faults and fracture belts. The fracture information reflected is more accurate and consistent with the imaging logging of the corresponding interval of the new well.