EAGE Workshop on Borehole Technologies - Pioneering Sustainable Solutions in Energy

During the construction of China’s first shale oil hydraulic fracturing test field, in order to systematically evaluate the scale and morphology of the fracturing fractures in the test wells, the coring well trajectory was optimized based on the distribution of microseismic events before drilling. In the subsequent comprehensive analysis process, the interpretation results of the coring well were analyzed for consistency with the microseismic events monitored during the previous fracturing process. Appropriate threshold values for microseismic event attributes were selected for screening, effective microseismic events were screened out, and the size of the effective fracture network was calculated. The regional microseismic interpretation model was optimized. Combined with 3D seismic attributes, seismic interpretation optimization based on the coring well was carried out to improve the interpretation accuracy. Finally, based on seismic and microseismic data, an analysis of the factors influencing the expansion of the hydraulic fracturing fracture network was conducted, and the morphology of the artificial fracture network formed by hydraulic fracturing was simulated.

In recent years, many risks arisen during the exploitation of geothermal resources, gas storage and CCUS, which can be detected effectively by long-term microseismic monitoring. However, most of microseismic processing methods was developed for short-term monitoring during hydro-fracturing, and has limitations of high acquisition costs and low automation when applied to the long-term monitoring. An automated processing flow based on machine-learning is established by this paper, meeting the application of long-term microseismic monitoring. This flow is applied to microseismic data of hot dry rock fracturing acquired by shallow borehole receivers, and benchmarked with the traditional processing method, verifying the reliability of machine-learning methods in long-term microseismic monitoring. Our result shows a high data quality of shallow bore-hole receivers. Compared with traditional methods, the denoising and phase picking methods based on neural network achieve much higher S/N ratio and PS picking accuracy. The wrong picks are excluded by automatic quality control method based on Gaussian Mixture Model effectively. And the relocation result is similar to the traditional method with manually quality control. Combined with shallow bore-hole receivers, the automatic processing flow in this study has a good potential in the long-term microseismic data processing.

This paper presents the application of the differential borehole-to-surface electromagnetic method to evaluate the distribution of remaining oil in ultra-deep carbonate reservoirs in western China. The method involves multiple excitations within the target formation, followed by differential processing of phase parameters to obtain a 3D data volume of differential phase anomalies. These anomalies are used to analyze the spatial distribution of residual oil, with a theoretical resolution of 5 meters vertically and ±12.5 meters laterally. The study, conducted in a reservoir at depths of 6,100 to 6,500 meters, demonstrates the method’s ability to distinguish fluid properties and effectively evaluate remaining oil distribution. Results from production wells validate the reliability of the electromagnetic predictions, highlighting the method’s high resolution and precision in ultra-deep oil exploration.

Effective prediction of formation fracture pressure plays an important role in analyzation of wellbore stability, rational hydraulic fracturing design, reservoir stimulation, and safe drilling operations. However, current methods such as rock sample fracture tests and logging data estimation have limitations of spatial discontinuity. Considering the impact of tectonic stress on the magnitude of horizontal in-situ stress, we propose a novel method obtaining three-dimensional fracture pressure based on seismic data in this paper. This method is applied to a thin reservoir layer in PZ gas field, which suffers well influxes, wellbore losses, block falls, and stuck pipe incidents because of complex geological conditions. After pre-stack seismic inversion, rock strength parameter prediction and formation pressure prediction, the predicted fracture pressure from seismic data coincide with the logging interpretation results, validating the feasibility and reliability of the proposed method. The application of the method provides reliable reference data for horizontal well design and fracturing operations in tight reservoirs.

Vertica seismic profiling (VSP) is a seismic exploration technique in which often features the receivers placed along the wellbore while the sources located at the surface. VSP signals include up/down-going P-waves, S-waves as well as converted-waves, scattering waves, multiple waves, etc. The suppression of VSP multiples is a crucial task in VSP data processing. the effectiveness of VSP multiple wave suppression directly affects the ability to identify thin reservoirs. it is necessary to study methods that can completely suppress VSP multiple waves. This abstract proposes a frequency domain depth-varying deconvolution method. By extracting wavelets at different depths in VSP data, frequency-domain wavelet shaping is achieved. The new method effectively suppresses multiples at various VSP depths, demonstrating superior suppression effectiveness compared to traditional approaches. The new deconvolution VSP records are free of multiples, which is more conducive to multiple identification and high-precision downhole imaging. Through the study of VSP frequency domain depth-varying deconvolution method, effective suppression of VSP multiple waves has been achieved, and ideal results have been obtained by processing simulated and actual VSP records. The frequency domain depth-varying VSP deconvolution method can effectively suppress VSP multiple waves, with better results than time-domain deconvolution.

Time-lapse borehole seismic is an important technology for reservoir dynamic monitoring. It is more advantageous to use optical fiber for time-lapse VSP data acquisition with high efficiency and high-quality data. Two periods of time-lapse DAS walkaway VSP data acquisition were completed in the eastern China oilfield. High signal-noise ratio, clear reflection of the target layer, and good consistency of VSP were obtained, which met the requirements of reservoir dynamic monitoring. Based on the consistency processing of amplitude and wavelet, wave field separation and other processing techniques, the consistency and efficiency of data processing are improved and the high-precision imaging section is obtained. By comparing the differences of amplitude, frequency attributes and wave impedance of VSP imaging in different periods, the change of oil saturation and other reservoir characteristic parameters with are analyzed.

China is rich in shale gas resources, but the geological conditions of shale reservoirs are complicated and faults are developed, especially the deep shale gas in Sichuan Basin. During hydraulic fracturing, complex geological conditions lead to frequent casing deformation, which can seriously affect the EUR in the area. The seismic fracture attribute is mainly used for casing deformation warning, but it still cannot meet the production demand. The fracture scale predicted by 3D seismic data cannot reach the fracture scale reflected by drilling and microseismic monitoring. The actual data in Sichuan Basin show that there is still a big difference between the 3D seismic fracture prediction results and the actual drilling results. Aiming at the problem of low accuracy of fracture prediction, this paper proposes a method to optimize 3D seismic fracture prediction by using the dynamic development results, and update the 3D seismic fracture prediction results by using the micro-seismic monitoring results of drilling and fracturing during the development process to improve the accuracy of fracture prediction. The dynamic development results are combined with the static seismic results.