Search Results (8)

The tight sandstone reservoirs of the Tarim Basin in China are characterized by vertically stacked multi-sweet spots. However, the strong vertical heterogeneity and discontinuity limit the effectiveness of hydraulic fracturing for multilayered co-production. To investigate the mechanisms governing the vertical cross-layer propagation of hydraulic fractures in the multilayered sandstone reservoir, outcrop rocks of fine sandstone and siltstone from the area were collected. Subsequently, these rocks were cemented to fabricate multilayered experimental samples with lithological transition zones. Hydraulic fracturing experiments were performed to systematically study fracture propagation behavior, with particular focus on the influence of interlayered lithology, vertical stress differences, fracturing fluid injection rate, and fluid viscosity on vertical fracture growth. Experimental results demonstrate that hydraulic fracturing in multilayered sandstone can form both passivated and cross-layer fracture networks while also activating lateral propagation along lithological transition zones. When hydraulic fractures extend from high-brittleness layers to low-brittleness layers, their vertical propagation is limited, promoting shear activation along lithological transition interfaces. As the vertical stress difference increases, the vertical propagation range of hydraulic fractures expands progressively, with fracture morphology evolving from a passivated type to a single-wing cross-layer pattern and further developing into a bi-wing cross-layer geometry. Increasing the injection rate and viscosity of the fracturing fluid enhances cross-layer fracture propagation while suppressing the activation of lithological transition zones. The insights derived from this study can provide a theoretical foundation and engineering guidance for the design and implementation of hydraulic fracturing in multilayered tight sandstone reservoirs in the Tarim Basin. Full article

Coalbed methane (CBM) reservoirs in southwestern China are characterized by thick, multi-layered coal sequences partitioned into several independent pressure systems by impermeable strata. Commingled production from multiple coal seams in such multi-superposed CBM systems often suffers from severe inter-layer interference, leading to suboptimal gas recovery. To address this challenge, we developed a systematic four-step optimization workflow integrating geological data screening, pressure compartmentalization analysis, and numerical reservoir simulation. The workflow identifies the key “main” coal seams and evaluates various co-production layer combinations to maximize gas recovery while minimizing negative interference. We applied this method to a CBM well (LC-C2) in the Western Guizhou–Eastern Yunnan region, which penetrates three discrete CBM pressure systems. In the case study, single-layer simulations first revealed that one seam (No. 7 + 8) contributed over 30% of the total gas potential, with a few other seams (e.g., No. 18, 13, 4, 16) providing moderate contributions and many seams yielding negligible gas. Guided by these results, we simulated five commingling scenarios of increasing complexity. The optimal scenario was to co-produce the seams from the two higher-pressure systems (a total of six seams) while excluding the low-pressure shallow seams. This optimal six-seam configuration achieved a 10-year cumulative gas production of approximately 2.53 × 10⁶ m³ (about 700 m³/day average)—roughly 75% higher than producing the main seam alone, and even about 15% greater than a scenario involving all available seams. In contrast, including all three pressure systems (ten seams) led to interference effects where the high-pressure seams dominated flow and the low-pressure seams contributed little, resulting in lower overall recovery. The findings demonstrate that more is not always better in multi-seam CBM production. By intelligently selecting a moderate number of compatible seams for co-production, the reservoir’s gas can be extracted more efficiently. The proposed quantitative optimization approach provides a practical tool for designing multi-seam CBM wells and can be broadly applied to similar geologically compartmentalized reservoirs. Full article

The synergistic development of low-permeability reservoirs such as deep coalbed methane (CBM) and tight gas has emerged as a key technology to reduce development costs, enhance single-well productivity, and improve gas recovery. However, due to fundamental differences between coal seams and tight sandstones in their pore structure, permeability, water saturation, and pressure sensitivity, significant variations exist in their flow capacities and fluid production behaviors. To address the challenges of production allocation and main reservoir identification in the co-development of CBM and tight gas within deep gas-bearing basins, this study employs the transient multiphase flow simulation software OLGA to construct a representative dual-gas co-production well model. The regulatory mechanisms of the gas–liquid distribution, deliquification efficiency, and interlayer interference under two typical vertical stacking relationships—“coal over sand” and “sand over coal”—are systematically analyzed with respect to different tubing setting depths. A high-precision dynamic production allocation method is proposed, which couples the wellbore structure with real-time monitoring parameters. The results demonstrate that positioning the tubing near the bottom of both reservoirs significantly enhances the deliquification efficiency and bottomhole pressure differential, reduces the liquid holdup in the wellbore, and improves the synergistic productivity of the dual-reservoirs, achieving optimal drainage and production performance. Building upon this, a physically constrained model integrating real-time monitoring data—such as the gas and liquid production from tubing and casing, wellhead pressures, and other parameters—is established. Specifically, the model is built upon fundamental physical constraints, including mass conservation and the pressure equilibrium, to logically model the flow paths and phase distribution behaviors of the gas–liquid two-phase flow. This enables the accurate derivation of the respective contributions of each reservoir interval and dynamic production allocation without the need for downhole logging. Validation results show that the proposed method reliably reconstructs reservoir contribution rates under various operational conditions and wellbore configurations. Through a comparison of calculated and simulated results, the maximum relative error occurs during abrupt changes in the production capacity, approximately 6.37%, while for most time periods, the error remains within 1%, with an average error of 0.49% throughout the process. These results substantially improve the timeliness and accuracy of the reservoir identification. This study offers a novel approach for the co-optimization of complex multi-reservoir gas fields, enriching the theoretical framework of dual-gas co-production and providing technically adaptive solutions and engineering guidance for multilayer unconventional gas exploitation. Full article

Tomato is a crop with high potential to be used in various food industry co-products, such as sauces. In addition to increasing the supply of differentiated products, processed foods have improved shelf life. However, as a consequence of thermal processing, there may be some important nutritional losses. In this context, the choice of suitable varieties for each type of processing based on the assessment of food losses is extremely important to both the processing industry and the consumer. Therefore, this work aimed to predict the percentage of concentration loss in tomatoes during cooking for sauce production using an artificial neural network (ANN). The prediction was made by analyzing the fresh fruit and comparing it to the cooked product. The study investigated bioactive compounds (vitamin C, ascorbic acid, phenolic compounds, flavonoids, carotenoids, anthocyanins, lycopene, and β-carotene), antioxidant activity (DPPH and FRAP), soluble solids, pH, titratable acidity, ratio, and total sugar. Nine commercial and non-commercial tomato varieties were evaluated. The artificial neural network used was the multilayer perceptron, and its results were compared with first-, second-, and third-degree polynomial regression techniques, evidencing its superiority. This superiority was confirmed by the higher correlation achieved using the ANN (R² = 0.9025), outperforming the first-, second-, and third-degree regressions (R² = 0.8817, 0.8819, and 0.8941, respectively). Furthermore, the ANN achieved a lower mean squared error (MSE = 0.000999) and strong validation performance, reinforcing its greater precision and reliability compared to traditional models. Full article

Increasing oil production is crucial for multilayer co-production. When there are significant differences in the permeability of each layer, an interlayer contradiction arises that can impact the recovery efficiency. After a number of tests and the establishment of a mathematical model, the effects of permeability contrast on oil production for water flooding were revealed. In the meantime, the developed mathematical model was solved using the Buckley–Lever seepage equation. Ultimately, the accuracy of the established model was confirmed by comparing the simulated outcomes of the mathematical model with the experimental results. The findings indicate that when permeability contrast increases, the production ratio of the high-permeability layer will improve. This is primarily due to the low-permeability layer’s production contribution rate decreasing. The accuracy of the established model is ensured by an error of less than 5% between the results of the experiment and the simulation. When the permeability contrast is less than three, the low-permeability layer can be effectively used for three-layer commingled production. However, when the permeability contrast exceeds six, the production coefficient of the low-permeability layer will be less than 5%, which has a significant impact on the layer’s development. Full article

Multilayered reservoirs with coexisting free gas and hydrates are primary targets for commercialization, nevertheless, the extremely low permeability greatly limits their extraction efficiency. Herein, multilayer commingled production using horizontal wells stimulated by hydraulic fracturing and thermal fluid injection was proposed to enhance productivity, and the effects of key factors on co-production performance were numerically examined, with the reservoir located in the Shenhu Area as the geological background. The results indicated that due to severe interlayer contradictions, the stimulation capabilities of using fracturing or thermal fluid injection alone were limited, in particular, the extraction of hydrates severely lagged behind. However, their combination exhibited tantalizing productivity due to strengthened inter-well interaction. Reducing the fracture spacing was more effective than increasing fracture conductivity in shortening the production cycle, and intensive fractures with adequate flow capacity were suggested for gas enhancement and water control. When the fracture spacing was reduced from 30 to 5 m and the fracture conductivity increased from 10 to 100 D·cm, the horizontal section length for commercial production (average daily gas production of 50,000 m³ and recovery ratio of 0.7) was reduced from 1758 to 146 m, which is lower than the on-site horizontal section length of 250–300 m. Therefore, the proposed development mode is promising for the commingled production of gas and hydrates. Full article

In coal seam gas (CSG) coproduction wells, due to the different production pressures of CSG production layer at different depths, the interlayer interference in wellbore seriously affects the gas production of a coproduction well. To effectively suppress the interlayer interference of the wellbore, a wellbore pressure distribution method for a two-layer coproduction well is proposed. Based on the analysis of the factors influencing the flow pressure distribution in the wellbore of two-layer coproduction wells, a method of coproduction flow pressure adjustment by regulating the wellhead pressure and the depth of the dynamic fluid level was established in this paper. The results show that wellhead pressure can directly affect the production pressure of two layers. The variation in layer 1 output mainly affects the pressure difference between the wellhead pressure and the pressure at the depth of layer 1, which has little effect on the pressure difference between layer 1 and 2. An increase in gas production from layer 2 would not only cause a pressure increase in layer 1, but also result in a reduction of the production pressure at layer 2. The maximum pressure gradient of the gas section is 0.14 MPa/100 m, and the pressure gradient of the gas–liquid section is 0.53–1.0 MPa/100 m. Full article

The majority of China’s multi-layer low permeability tight gas reservoirs are currently being extracted through the method of multi-layer co-production. However, due to the significant disparity in physical properties and varying degrees of pressure depletion among the production layers, elucidating the primary factors influencing the productivity contribution of each gas layer remains challenging. A multi-factor analytical model is proposed for commingled gas wells with multiple layers. An unstable model is established for the production of commingled layers, and the problem of flow distribution is addressed using the Duhamel convolution principle. The Laplace transform is subsequently employed to derive the solution in the Laplace domain, which can be inverted utilizing the Stehfest inversion algorithm to obtain a real-time domain solution. The influence of reservoir factors on the stratification contribution rate has been comprehensively analyzed, encompassing permeability, porosity, initial pressure, drainage radius, and layer thickness. The orthogonal test design was employed to conduct range analysis and variance analysis separately, yielding the primary and secondary order as well as influence weight of the five factors. The findings demonstrate that, within this gas reservoir, the discharge radius, thickness, and porosity are identified as the primary factors influencing gas well productivity. Furthermore, seven horizontal flow charts illustrating the double-layer gas reservoir and five horizontal flow charts depicting single-factor variations in the double-layer gas reservoir were constructed. These charts provide a clear visualization of the impact of each reservoir factor on stratification’s contribution rate. In contrast to previous studies, this novel approach presents a comprehensive optimization framework that ranks the influence weights of individual factors and identifies the most significant factors impacting multi-layer gas reservoirs. The presented method also serves as a foundation for the subsequent selection of multi-layer gas reservoirs, formulation of gas well stimulation measures, and efficient development. Full article