Lost circulation is a critical technical challenge in drilling engineering. Current laboratory simulations of fracture-induced lost circulation primarily rely on traditional methods such as steel plate fractures，metal sheets，and sand beds，which fail to adequately replicate complex characteristics of actual thief zones，including the fracture orientation，tortuosity，and surface roughness. As a result，the field application success rate of plugging materials under complex geological conditions is still generally low. This paper proposes an innovative method that integrates realistic fracture simulation of thief zones with 3D printing technology through 3D imaging reconstruction. Actual rock samples of thief zones are scanned to establish digital core models，and 3D printing is applied to creating simulated cores，which significantly improves the fidelity and compatibility to real fracture structures. On this basis，a customized high temperature high pressure dynamic circulation plugging apparatus is used to conduct systematic pressure bearing experiments of multi-scale composite fractures. The sealing performance of various plugging formulations are compared and analyzed between 3D printed cores and traditional steel plate fractures，and a new methodology applicable to realistic fracture simulation and plugging evaluation is constructed. Field testing has validated that the optimized plugging formulation presents a one-time success rate of 83%，significantly enhancing the operational feasibility and economic viability of plugging operations. This method provides effective technical support for the efficient and precise sealing of complex formation fractures and contributes substantially to improved drilling efficiency and security of oil and gas resource recovery.

The investment estimation of a systematic drilling engineering project is an important step for oilfield enterprises to strengthen investment control and enhance operation management. The quality of investment estimation does not only decide the feasibility and profitability of the development plan，but also has an important instruction influence on the implementation and operation performance of the approved engineering plan. This paper proposed a method for extracting engineering parameters of drilling investment estimation based on the natural language processing algorithm and the Monte Carlo simulation investment prediction model. These two techniques were introduced into the petroleum engineering estimation，and it was demonstrated via modelling and case studies that all selected control factors were significant and thus effective. Based on the above，the investment estimation was carried out. Natural language processing algorithms were required for parameter extraction and processing，with an accuracy of over 90%. Meanwhile，the Monte Carlo simulation investment prediction model was used for calculation to ensure that the error between the extreme investment and the existing economic evaluation results was less than 5%. This developed method has been successfully applied to 29 production capacity building projects in 2024，identifying and warning 8 projects with excessive investment. It improves the accuracy and efficiency of engineering parameter extraction，enhances the percent of pass for the internal rate of return of petroleum drilling engineering investment estimation，and is of great help in improving the digitalization level of the petroleum engineering estimation.