Diagenetic Fluid and Its Impact on Sandstone Reservoirs in the Southern Boxing Sag, Dongying Depression, Bohai Bay Basin, China

Diagenesis typically exerts a crucial impact on the formation of high-quality sandstone reservoirs in the Eocene Shahejie Formation, Dongying Depression. To better understand the formation process of petrophysical properties, this research conducts petrographic and geochemical analyses to investigate the nature of diagenetic fluids. Petrographic observations suggest that the dominant cements are carbonate, authigenic quartz, and clay minerals, accompanied with the dissolution of feldspar and calcite. The homogenization temperature of aqueous inclusions in quartz overgrowth usually exceeds 90°C corresponding to the maturity of organic matter. Quartz overgrowths contain higher amounts of CaO and Al2O3 than detrital quartz. This indicates that the siliceous fluid mainly originates from the dissolution of feldspar. Moreover, the conversion of clay minerals also provides trace amounts of silica into pore water during the burial process. Carbonate cements consist of early-stage calcite as well as late-stage Fe-calcite and ankerite. Calcite with relatively higher MnO proportions shows yellow luminescence and dissolution signs. Fe-calcite and ankerite cements have a higher homogenization temperature than that of quartz overgrowth and mainly concentrate in FeO and MgO as well as contain a small amount of Na+, K+, and Sr2+. The rare earth element (REE) pattern of bulk mudstone and carbonate cements as well as C–O isotopic evidences indicate that the diagenetic fluids of carbonate cementation are primarily controlled by the adjacent mudstone, whereas mineral dissolution and altered clay minerals in sandstone provide additional cations for the local reprecipitation of late-stage carbonate. Therefore, diagenetic fluids within sandstone reservoirs are typically subject to alkaline–acid–alkaline conditions and are influenced by internal sources in a closed system. Compaction significantly reduces the pore space of sandstone reservoirs in the Boxing Sag. Carbonate cementation further increases the complexity of pore structure and obeys the principle of mass balance.

Permeability Predictions for Tight Sandstone Reservoir Using Explainable Machine Learning and Particle Swarm Optimization

High-precision permeability prediction is of great significance to tight sandstone reservoirs. However, while considerable progress has recently been made in the machine learning based prediction of reservoir permeability, the generalization of this approach is limited by weak interpretability. Hence, an interpretable XGBoost model is proposed herein based on particle swarm optimization to predict the permeability of tight sandstone reservoirs with higher accuracy and robust interpretability. The porosity and permeability of 202 core plugs and 6 logging curves (namely, the gamma-ray (GR) curve, the acoustic curve (AC), the spontaneous potential (SP) curve, the caliper (CAL) curve, the deep lateral resistivity (RILD) curve, and eight lateral resistivity (RFOC) curve) are extracted along with three derived variables (i.e., the shale content, the AC slope, and the GR slope) as data sets. Based on the data preprocessing, global and local interpretations are performed according to the Shapley additive explanations (SHAP) analysis, and the redundant features in the data set are screened to identify the porosity, AC, CAL, and GR slope as the four most important features. The particle swarm optimization algorithm is then used to optimize the hyperparameters of the XGBoost model. The prediction results of the PSO-XGBoost model indicate a superior performance compared with that of the benchmark XGBoost model. In addition, the reliable application of the interpretable PSO-XGBoost model in the prediction of tight sandstone reservoir permeability is examined by comparing the results with those of two traditional mathematical regression models, five machine learning models, and three deep learning models. Thus, the interpretable PSO-XGBoost model is shown to have more advantages in permeability prediction along with the lowest root mean square error, thereby confirming the effectiveness and practicability of this method.

Minimizing Formation Damage in Drilling Operations: A Critical Point for Optimizing Productivity in Sandstone Reservoirs Intercalated with Clay

The recovery of oil and gas from underground reservoirs has a pervasive impact on petroleum-producing companies’ financial strength. A significant cause of the low recovery is the plugging of reservoir rocks’ interconnected pores and associated permeability impairment, known as formation damage. Formation damage can effectively reduce productivity in oil- and gas-bearing formations—especially in sandstone reservoirs endowed with clay. Therefore, knowledge of reservoir rock properties—especially the occurrence of clay—is crucial to predicting fluid flow in porous media, minimizing formation damage, and optimizing productivity. This paper aims to provide an overview of recent laboratory and field studies to serve as a reference for future extensive examination of formation damage mitigation/formation damage control technology measures in sandstone reservoirs containing clay. Knowledge gaps and research opportunities have been identified based on the review of the recent works. In addition, we put forward factors necessary to improve the outcomes relating to future studies.

A Comprehensive Model Integrating the Stress Sensitivity for Pressure Transient Behavior Study on the Two-Zone System for Offshore Loose Sandstone Reservoirs

Permeability changes in the weakly consolidated sandstone formation, caused by sand migration, has a serious impact on the interpretation of well testing and production prediction. In this article, a two-zone comprehensive model is presented to describe the changes in permeability by integrating the produced sand, stress sensitivity characteristics. In this model, inner zone is modeled as a higher permeability radial reservoir because of the sand migration, while the outer zone is considered as a lower permeability reservoir. Besides, non-Newtonian fluid flow characteristics are considered as threshold pressure gradient in this paper. As a result, this bi-zone comprehensive model is built. The analytical solution to this composite model can be obtained using Laplace transformation, orthogonal transformation, and then the bottomhole pressure in real space can be solved by Stehfest and perturbation inversion techniques. Based on the oilfield cases validated in the oilfield data from the produced sand horizontal well, the flow regimes analysis shows seven flow regimes can be divided in this bi-zone model considering stress sensitive. In addition, the proposed new model is validated by the compassion results of traditional method without the complex factors. Besides, the effect related parameters of stress sensitivity coefficient, skin factor, permeability ratio and sanding radius on the typical curves of well-testing are analyzed. This work introduces two-zone composite model to reflect the variations of permeability caused by the produced sand in the unconsolidated sandstone formation, which can produce great influence on pressure transient behavior. Besides, this paper can also provide a more accurate reference for reservoir engineers in well test interpretation of loose sandstone reservoirs.