New Method for Characterizing Internal Structure of Fault-Karst Reservoirs and Analysis on Acidizing Fracturing Effect: A Case Study in HLHT Oilfield, Tarim Basin, NW China

Abstract

Superimposed tectonic movement and karst erosion resulted in a combination of fractures and irregular caves in deep/ultradeep carbonate rocks, typically along major fault swarms. Outlining these fault-karst reservoirs mainly depends on recognizing the strong reflection in seismic profiles; however, characterizing their internal structures is still difficult, which are represented as weak amplitude in seismic profiles. This study intended to propose a method to dissect the internal structure of fault-karst reservoirs, which contains four steps: (1) elimination of the signal interference by the covering bed with strong energy and recognition of internal reservoirs with low energy based on seismic data conversion, frequency division, and inversion; (2) gradient structure tensor analysis based on an anisotropic Gaussian filter for fault-karst reservoir outlining; (3) internal faults and cave recognition on the basis of wave-based inversion; and (4) reevaluation of the number and scale of these faults and caves based on seismic recognition and well test results and verification of their volumes and hydrocarbon reserves. The method was used in the evaluation of the fault-karst reservoir in the Halahatang (HLHT) oilfield, which is located in the north of Tarim Basin. The results show that the fault-karst reservoirs along major faults and their internal structures are effectively recognized, and the error of the predicted depth of the reservoirs decreases from more than 20 m before to less than 4 m now; the drilling success ratio increases from 70% to 90%. In addition, the method supports the recognition of untapped fault-karst reservoirs around shut-in wells, which provides guidance for sidetracking plans. Further, by comparing the geophysical volume of fault-karst reservoirs and the reserve predicted by production performance, the untapped reserve in a certain reservoir can be evaluated; on this basis, producing wells received high yields by targeted acid fracturing. In summary, the method effectively improves the prediction accuracy and the recovery efficiency of fault-karst reservoirs.

Study on Residual Oil Distribution Law during the Depletion Production and Water Flooding Stages in the Fault-Karst Carbonate Reservoirs

“…In addition, the large and small fractures are characterized by the presence of large and small hydrocarbon production capacities, respectively, while zones with a lack of fractures are characterized by a lack of hydrocarbon reservoirs [26,27]. Different fault-karst reservoirs along the same fracture zone are characterized by segmental accumulation, differential enrichment, and different developmental features [28,29]. The size and connectivity of fault-karst segments control the distribution and scale of the reservoirs.…”

Deep carbonate fault–karst reservoir characterization by multi‐task learning

“…Moreover, several researchers studied fault-karst using multiple different types of methods. Cao et al (2021) focused on the internal structural characteristics of the fault-karst reservoir. They detected the outlining of fault-karst using the gradient structure tensor analysis and depicted the internal structure of fault-karst on the basis of the wave-based inversion.…”