There are similarities and differences in employing amplitude variation with offset (AVO) to explore for gas-sand reservoirs, as opposed to coal-bed methane (CBM) reservoirs. The main similarity is that large Poisson's ratio contrasts, resulting in AVO gradient anomalies, are expected for both kinds of reservoirs. The main difference is that cleating and fracturing raise the Poisson's ratio of a coal seam as it improves its reservoir potential for CBM, while gas always lowers the Poisson's ratio of a sandstone reservoir. The top of gas sands usually has a negative AVO gradient, leading to a class one, two, or three anomaly depending on the impedance contrast with the overlying caprock. On the other hand, the top of a CBM reservoir has a positive AVO gradient, leading to a class four anomaly. Three environmental factors may limit the usage of AVO for CBM reservoirs: the smaller contrast in Poisson's ratio between a CBM reservoir and its surrounding rock, variations in the caprock of a specific CBM reservoir, and the fact that CBM is not always free to collect at structurally high points in the reservoir. However, other factors work in favor of using AVO. The strikingly high reflection amplitude of coal improves signal/noise ratio and hence the reliability of AVO measurements. The relatively simple characteristics of AVO anomalies make them easy to interpret. Because faults are known to improve the quality of CBM reservoirs, faults accompanied by AVO anomalies would be especially convincing. A 3D-AVO example offered in this paper shows that AVO might be helpful to delineate methane-rich sweet spots within coal seams.

Carbon Capture, Utilization and Storage, also referred to as Carbon Capture, Utilization and Sequestration (CCUS), is one of the novel climate mitigation technologies by which CO₂ emissions are captured from sources, such as fossil power generation and industrial processes, and further either reused or stored with more attention being paid on the utilization of captured CO₂. In the whole CCUS process, the dominant migration pathway of CO₂ after being injected underground becomes very important information to judge the possible storage status as well as one of the essential references for evaluating possible environmental affects. Interferometric Synthetic Aperture Radar (InSAR) technology, with its advantages of extensive coverage in surface deformation monitoring and all-weather traceability of the injection processes, has become one of the promising technologies frequently adopted in worldwide CCUS projects. In this study, taking the CCUS sequestration area in Shizhuang Town, Shanxi Province, China, as an example, unmanned aerial vehicle (UAV) photography measurement technology with a 3D surface model at a resolution of 5.3 cm was applied to extract the high-resolution digital elevation model (DEM) of the study site in coordination with InSAR technology to more clearly display the results of surface deformation monitoring of the CO₂ injection area. A 2 km surface heaving dynamic processes before and after injection from June 2020 to July 2021 was obtained, and a CO₂ migration pathway northeastward was observed, which was rather consistent with the monitoring results by logging and micro-seismic studies. Additionally, an integrated monitoring scheme, which will be the trend of monitoring in the future, is proposed in the discussion.

Carbon neutrality is a goal the world is striving to achieve in the context of global warming. Carbon capture and storage (CCS) has received extensive attention as an effective method to reduce carbon dioxide (CO₂) in the atmosphere. What follows is the migration pathway and leakage monitoring after CO₂ injection. Interferometric synthetic aperture radar (InSAR) technology, with its advantages of extensive coverage in surface deformation monitoring and all-weather traceability of the injection processes, has become one of the promising technologies frequently adopted in worldwide CCS projects. However, there is no mature evaluation system to determine whether InSAR technology is suitable for each CO₂ sequestration area. In this study, a new evaluation model is proposed based on the eight factors that are selected from the principle of the InSAR technique and the unique characteristics of the CO₂ sequestration area. According to the proposed model, the feasibility of InSAR monitoring is evaluated for the existing typical sequestration areas in the world. Finally, the challenges and prospects of InSAR in the CCS project are discussed.

CO₂ geological storage projects are an essential tool for China to achieve the double carbon target of energy savings and emission reductions. In order to safely and effectively control the implementation of injection projects and monitor the dynamics of CO₂ injection, multi-dimensional and multi-disciplinary monitoring tools are required. Among them, microseismic monitoring is a key technology for predicting reservoir dynamics and reflecting reservoir geomechanical behavior. Such monitoring has been carried out previously for reservoirs in other countries, but experimental projects are also gradually being developed in China. In this paper, we focus on the research and analysis results of microseismic monitoring of carbon storage projects in various work areas. For different reservoir conditions, we explore combinations of the monitoring implementation methods in China, comparing the differences in each work area. We propose a joint well and ground microseismic monitoring method and a multi-spatial and multi-physical field coupling research system for use in the implementation of domestic demo projects for the future research and development of microseismic monitoring of carbon storage projects. The monitoring program can meet the requirements for certain periodic repeated or continuous observations and can intelligently assess the risk and handle the alert behavior. The foundation is laid for the development of the future microseismic monitoring technology to achieve the goal of developing cost-controllable, permanent, and real-time monitoring equipment. The application of the monitoring system in China has been effective, and this experience can contribute to the development of injection engineering in the future.

An ultradeep, faulted karst reservoir of Ordovician carbonate was discovered in the Shunbei area of the Tarim Basin. Fractured-cavity reservoirs buried beneath the large thickness of upper Ordovician mudstone were formed along the fault-karst belts. The hydrocarbon accumulation in these reservoirs is controlled by the fault system, and the oil-gas accumulation was affected by karstification and hydrothermal reformation. Previous studies and 2D modeling revealed that the reservoirs had “bright spot” amplitude responses like “string beads,” and they have developed along the strike-slip faults. However, describing such a complex fault-controlled karst system is still a difficult problem that has not been well addressed. We have sought to instruct the attribute expression of faulted karst reservoirs in the northern part of the Tarim Basin. We applied coherence and fault likelihood (FL) seismic attributes to image faults and fractures zones. We then used a trend analysis method to calculate the residual impedance from the impedance of the acoustic inversion, using the fact that residual impedance has higher lateral resolution in reservoir predictions. Finally, we integrated the coherence, FL, and residual impedance attributes into a new seismic attribute, the “fault-vuggy body,” with a certain fusion coefficient. The fault-vuggy body attribute establishes a connection between faults and karst cavities. This method could help in the characterization and prediction of carbonate faulted karst reservoirs. Available drilling data were used to validate that the fused fault-vuggy body attribute was an effective reservoir prediction method. As the seismic sections and slices along the layer help delineate, the distribution of bright spots and strike-slip faults indicates that the main strike-slip fault zones are the most favorable reservoirs in the Shunbei Oil and Gas Field.