The effects of CO₂-water-rock interactions on the injectivity and safety of CO₂ geological storage have drawn wide attention. The geochemical reaction mechanisms in carbonate formations after CO₂ injection are still controversial. To better understand the transformation of injected CO₂ in carbonates and the involved geochemical reactions, we first conducted autoclave experiments reproducing the in-situ conditions of the Lianglitage Formation, Yingshan Formation, and Qiulitage Formation at the Tazhong Uplift in the Tarim Basin. We then established a batch model using TOUGHREACT-ECO2H, validated with the experimental results, to simulate the long-term CO₂-water-rock interactions. It was found that the initial mineral compositions and water chemistry have important effects on the CO₂-water-rock interactions in carbonate formations. The experiment results show that the dissolution of calcite and dolomite dominates in the early reaction period. However, we still observed some secondary minerals, such as ankerite, montmorillonite, calcite, and dolomite. The CO₂-water-rock reactions can be more dramatic when the contents of calcite and dolomite in carbonates are closer. Moreover, the long-term simulation results show that calcite, magnesite, and hematite are the main formed secondary minerals, whereas dolomite is the major dissolved mineral. This study is helpful for a better understanding of the CO₂ mineral trapping mechanism in carbonate formations.

Lithofacies identification is essential in reservoir evaluation, especially in ultradeep carbonate reservoirs. In general, coring samples are the best sources to identify carbonate lithofacies because they are taken directly from reservoirs. However, the core is expensive to obtain, and generally its availability is greatly limited. In recent years, deep learning has attracted enormous attention because of its robust nonlinear regression and classification ability. This study applies a deep-learning algorithm to identify the lithofacies using geophysical well-log data. Six types of well-log data, such as natural gamma ray, density (DEN), neutron porosity (CNL), acoustic (AC), and shallow and deep lateral resistivity well logs (RT/RXO), are smoothed by the average sliding method and converted to 2D data. Then, the 2D data are treated as inputs to predict the carbonate lithofacies through the convolutional neural network (CNN). The results indicate that the prediction accuracy rate is 90.2%. This indicates that the CNN can identify different carbonate lithofacies well.

Deciphering the evolution of spatial geometry of carbonate platforms in deeply buried successions is still a challenge due to the low resolution of seismic data and the constraints of drilling wells. In this study, by combining a seismic forward model, we systematically delineated the external morphology and internal architecture of seismic reflection and established a depositional model of a carbonate platform. The Lower Paleozoic strata display the high-amplitude reflection in the Lower-Middle Cambrian interval and the low-amplitude reflection in the Upper Cambrian-Middle Ordovician interval. The high-amplitude reflection interval thins or wedges out towards the center of the present Southwest Depression section, and thickens to the north and south. Inside of the high-amplitude interval, the seismic reflection terminated at the top reflector. Seismic forward modeling was performed to examine the validity of possible hypothetical models in the studied area. The modeling results show that the simulated stratigraphic patterns are comparable to a ramp or depression geometry which is well fit to the characteristics of actual seismic reflections. Such a ramp or depression geometry is built upon the changes in sea level and climate during the Cambrian period. This study emphasizes the potential of the integration of sequence stratigraphic analyses and seismic forward modeling as a seismic workflow for retrieving the stratigraphic architecture and platform geometry.

The Late Ediacaran Dengying Formation in the Sichuan Basin is a key target for deep-gas exploration, yet the controls on facies differentiation in the Penglai area, on the northern slope of the Central Sichuan Paleo-Uplift, remain debated. This study integrates 3D seismic data, well logs, cores, and thin sections from 20 wells to characterize the microfacies, microfacies associations, and sedimentary architecture of the Dengying Formation. Nine microfacies types are recognized and grouped into three microfacies associations: tidal flat, mound–shoal complex, and inter-mound. The same nine microfacies types occur in both members, but the mound–shoal complex association in the third and fourth members is more grain-rich, more strongly overprinted by recrystallization, and makes up meter-scale shallowing-upward cycles. The lateral variations in microfacies types across the study area are minor; facies differentiation is instead expressed through variations in microfacies associations and their cumulative thicknesses. Facies distribution analysis and 3D seismic paleogeomorphology demonstrate that the Penglai area developed a broad, gently NW-dipping carbonate ramp without distinct slope breaks, in contrast with the previously proposed rimmed platform model of the Gaoshiti–Moxi area. Within this ramp, mound–shoal complexes record large-scale lateral migration driven by high-frequency relative sea-level fluctuations, but their along-strike continuity is constrained by NE-trending basement faults oriented sub-perpendicular to the NW-trending rift axis. A hierarchical three-level control on facies differentiation is proposed: regional paleogeomorphology provides the first-order NW-dipping ramp framework; syn-sedimentary basement faults impose a second-order segmentation; and high-frequency sea-level fluctuations drive the third-order stacking patterns. This hierarchical mechanism refines the sedimentary model of the Dengying Formation and provides a predictive basis for delineating high-quality reservoir targets along the northern slope of the Central Sichuan Paleo-Uplift.

Recently, a series of prolific fracture-vug reservoirs have been discovered in the lower Ordovician dolostone successions of the northern Tarim Basin. However, the genesis of these reservoirs remains unclear. In this study, observations on drilling cores and thin sections identify the pore space characterized by dissolved fractures, fissures, and vugs. Petrology, cathodoluminescence, and homogenization temperatures of fluid inclusions aid in establishing the diagenetic paragenetic sequence. Dissolving enlargement occurred after chemical compaction of overlying limestone and before the Permian volcanic activity. Breccia pores containing unique fillings of terrestrial materials (quartz sand and allogenic kaolinite) and calcite cements with negative δ¹⁸O_PDB values (−18.4‰) along with ⁸⁷Sr/⁸⁶Sr ratios (up to 0.71026) indicate that the dissolving fluid originated from meteoric freshwater at the surface. The δ¹⁸O_SMOW values of the calcite precipitating fluid (−2.1‰ to −8.7‰) further suggest freshwater as the source of the dissolving fluid, buffered by the Ordovician wall rocks or formation water. As the distance from the unconformity surface increases, both the homogenization temperature and δ¹⁸O_PDB values of the breccia pore-filling calcite in the southern study area gradually elevate and deplete, respectively, indicating a rise in temperature during the infiltration of meteoric freshwater with increasing subsurface temperatures. The abnormal reflection bodies identified as reservoirs in seismic profiles along deep-seated strike-slip faults delineate these faults as the channel for the infiltration of meteoric freshwater. The penetrating strata of these faults and the high ⁸⁷Sr/⁸⁶Sr values of breccia pore-filling calcite suggest that karstification occurred during the Devonian period. Accordingly, we establish a deep karst model in which the Devonian meteoric freshwater penetrated along the strike-slip faults and dissolved the Ordovician dolostones, resulting in the development of deep buried karstic fault reservoirs in the southern region of the northern Tarim Basin.