Electrical borehole imaging tools cannot achieve full-borehole images due to their structure limitation. Gaps always occur between pads, and it is necessary to fill in the gaps for subsequent interpretation. In this paper, an improved model for borehole image restoration and enhancement is established by combining a “Deep-Fill” image repair algorithm based on generative adversarial networks (GANs) with histogram equalization principles. Firstly, resistivity data is converted into images, and the anomalous areas are manually repaired. Then, the manually repaired images undergo iterative training using the “Deep-Fill” model. Finally, the repaired images are further enhanced through histogram equalization principles. Results show the overall restoration quality of the model surpasses that of the original GAN-based restoration model, particularly in terms of texture coherence at junctions. This approach not only enhances the quality of repaired images but also improves the interpretability of geological features of the electrical imaging logs.

Wireline Formation Testing is an important technique in the oil field of exploration and development. Not only it can make real fluid samples of the formation directly obtained to know exactly oil existed in formation or not; but it can also show flowing pressure change to see the production capacity of the formation. So it is important measurement for formation evaluation during the drilling process and supports for activities of the exploration and development in the oil field. A numerical simulation model in this article is researched and established based on the Finite Volume Method with considering the influence of sensitive parameters such as reservoir heterogeneity, probe suction area, and mud-filtrate invasion depth during the drilling. The model is capable to design and evaluate for formation fluid sampling operations with calculating hydrocarbon content and flowing pressure. Furthermore, through case application, the performance and effect in the process of Wireline Formation Testing was demonstrated. The results indicate that this technology can be served as an effective auxiliary tool for fluid sampling operations with the function of optimizing fluid sampling measures. It can improve the accuracy of predicting indicators such as hydrocarbon content and breakthrough time during the sampling process. This study provides important backups and technical guidance for professionals in geological exploration and oilfield development.

Wireline formation testing is an important technique in the exploration and development of oil fields. Not only can real fluid samples be prepared from the formation directly obtained to know exactly whether the oil existed in the formation or not, but it can also show flowing pressure change to determine the production capacity of the formation. So, it is an important measurement method for formation evaluation during the drilling process and supports activities related to the exploration and development of oil fields. A numerical simulation model in this article is researched and established based on the finite volume method considering the influence of sensitive parameters such as reservoir heterogeneity, probe suction area, and mud-filtrate invasion depth during the drilling. The model is capable of designing and evaluating formation fluid sampling operations by calculating hydrocarbon content and flowing pressure. Furthermore, through case application, the performance and effect of the process of wireline formation testing were investigated. The results indicate that this technology can serve as an effective auxiliary tool for fluid sampling operations with the function of optimizing fluid sampling measures. It can improve the accuracy of predicting indicators such as hydrocarbon content and breakthrough time during the sampling process. This study provides important supporting evidence and technical guidance for professionals in geological exploration and oil field development.