Search Results (38)

After prolonged development, offshore edge- and bottom-water reservoirs have entered an ultra-high water-cut stage. Under long-time multilayer commingled production conditions, accurate dynamic quantification of layer-wise production remains technically challenging, and conventional production allocation approaches often lack the accuracy required for fine-scale reservoir management. To address these challenges, this study proposes a production allocation method that integrates static reservoir properties, dynamic production performance, and pressure-based correction. The resulting layer-wise allocation provides a quantitative basis for evaluating remaining oil utilization and delineating the distribution of remaining oil across individual layers. The method is formulated on the basis of a pseudo-steady-state productivity model that incorporates wellbore imperfection effects. The initial production rate of each layer is calculated by combining reservoir transmissibility with production pressure drawdown. To account for unequal pressure responses among layers under commingled production—resulting from pressure imbalance, limited edge- and bottom-water energy support, and interlayer interference—a correction factor is introduced to adjust the effective production contribution of low-pressure layers. Compared with the PLT test results, the average error of the conventional KH method was 16.7%, whereas the average error of the proposed method was reduced to 6.1%. The average error was reduced from 16.7% to 6.1%, corresponding to a 63.5% reduction in prediction error, indicating that the proposed approach can provide a more reliable estimation of layered production contribution. The proposed method enables continuous and dynamic production allocation for commingled wells without the need for frequent surveys, offering a practical tool for identifying multilayer production imbalance, evaluating remaining potential, and supporting development optimization in offshore oilfields. Full article

To address the pronounced interlayer productivity disparity and uneven reserve utilization during the development of multilayer low-permeability porous carbonate gas reservoirs, the G gas field on the right bank of the Amu Darya River was selected as the study area. Core-parallel physical simulation experiments, orthogonal numerical simulations, and production logging test (PLT) data were integrated to investigate the mechanisms of interlayer interference and its key controlling factors under multilayer commingled production. The results show that interlayer interference is primarily controlled by the permeability contrast and production differential. With increasing permeability contrast, high-permeability layers contribute a larger proportion of total production, whereas the utilization of medium- and low-permeability layers declines, thereby intensifying interlayer interference. Under the same permeability configuration, the interference coefficient increases with increasing production differential. Moreover, compared with the two-layer commingled-production cases, the three-layer system showed a stronger response to pressure-differential variation. When the production differential increased from 1 MPa to 5 MPa, the interference coefficient in the three-layer system increased from 9.84% to 27.83%, indicating more pronounced productivity loss in the medium- and low-permeability layers. Orthogonal numerical simulation indicates that the sensitivity of the main controlling factors follows the order of production differential ≥ permeability ratio > thickness ratio > gas viscosity. PLT data further validate the reliability of the experimental and numerical simulation results. During the development of Well G-22, the XVac layer consistently dominated gas production, whereas the XVm and XVp layers acted as supplementary contributors, indicating a dynamic production pattern in which high-permeability layers are preferentially activated and medium- and low-permeability layers contribute progressively at later stages. These findings demonstrate that permeability heterogeneity is the fundamental cause of interlayer interference, while the production differential serves as an important amplifying factor. This study provides a theoretical basis for zonal production allocation, optimization of the production differential, and stable production management in multilayer low-permeability porous carbonate gas reservoirs. Full article

This scoping review examines bovine respiratory disease (BRD) risk factors across beef production systems to clarify their contribution to disease occurrence and outcomes and to identify gaps that limit effective prevention. Following the PRISMA-ScR guidelines, eight databases (EBSCOhost, Google Scholar, MDPI, PubMed, ScienceDirect, Journal of Animal Science, Journal of Dairy Science, and Web of Science) were searched for peer-reviewed studies published between 2004 and 2024, yielding 91 eligible studies from 133 screened articles. Data were charted to assess how BRD risk factors have been investigated across cow–calf, stocker/backgrounding, and feedlot systems and categorized into biological, operational, and environmental domains. Twenty-three major risk factors were identified, with transportation stress and commingling most frequently studied in stocker and feedlot systems, while management-related factors such as vaccination were more commonly emphasized in cow–calf operations. The evidence base was heavily skewed toward feedlot populations (62%), with limited focus on cow–calf (13%) and stocker (7%) systems and few longitudinal studies spanning multiple production stages. Overall, the findings reveal substantial heterogeneity in research emphasis and highlight critical gaps in early-life and cross-stage risk assessment. These findings underscore an urgent need for longitudinal, cross-stage cohort studies and standardized BRD surveillance frameworks to address the early-life evidence gap and provide a foundation for more effective, data-driven, integrated disease prevention strategies. Full article

During multi-layer commingled production of coalbed methane (CBM), fluid interference induced by interlayer pressure differences is a major constraint on productivity, representing a dynamic coupling process of reservoir pressure, temperature, and deformation. To elucidate this mechanism, we constructed a four-layer superimposed reservoir physical model using a self-developed large-scale true triaxial multi-field coupling test system, which reflects the geological conditions of the Eastern Yunnan and Western Guizhou region. We precisely regulated interlayer pressure differences and monitoring multi-physical parameters in real time to analyze the dynamic evolution of reservoir temperature, pressure, and deformation fields. The findings reveal that: (1) Increased interlayer pressure difference intensifies fluid interference in low-pressure reservoirs, causing abnormal pressure buildup. For example, when the pressure difference rose from 0.2 MPa to 0.6 MPa, the maximum pressure increase in Reservoir I grew from 1.03 MPa to 1.13 MPa. (2) The high-pressure reservoir (Reservoir IV) remained largely unaffected throughout production, with its temperature decline rate consistently correlated positively with pressure difference, indicating a distinct response behavior. (3) Reservoir deformation correlates positively with initial pressure. When the initial pressure of Reservoir II increased from 1.2 MPa to 1.6 MPa, its volumetric strain rose from 1.81‰ to 2.21‰, attributable to the combined effects of matrix shrinkage, elevated effective stress, and desorption-induced thermal cooling. This study demonstrates how interlayer pressure differences regulate the coupled evolution of reservoir pressure, temperature, and deformation, providing experimental evidence and theoretical support for identifying interference mechanisms and optimizing development strategies in CBM commingled production. Full article

Bovine respiratory disease (BRD) remains one of the most consequential health and economic challenges in U.S. beef production, particularly within integrated systems where microbial, environmental, and management factors intersect. This review synthesizes contemporary epidemiological insights, emphasizing BRD’s multifactorial pathogenesis driven by dynamic host–pathogen–environment interactions involving agents such as Mannheimia haemolytica, Pasteurella multocida, and Mycoplasma bovis, alongside stressors from transportation, weaning, and commingling. BRD imposes annual losses exceeding two billion dollars through diminished feed efficiency, reduced carcass yield, increased treatment costs, and mortality. Despite progress in vaccination, biosecurity, and therapeutic interventions, BRD persists due to diagnostic subjectivity and limitations of traditional control measures. The review underscores emerging innovations, including precision livestock technologies, AI-enabled surveillance, and metabolomic biomarkers as transformative tools for early detection and targeted mitigation, while noting barriers related to cost, data harmonization, and scalability. The rising threat of antimicrobial resistance further highlights the need for stewardship frameworks that balance therapeutic effectiveness and public health priorities. Additionally, the paper analyzes policy and economic considerations, arguing for coordinated efforts among producers, veterinarians, researchers, and regulators. BRD is reframed as a systems-level challenge requiring integrated scientific, operational, and regulatory strategies to enhance resilience and sustainability across U.S. beef production. Full article

To investigate the interlayer interference mechanism during multi-layer commingled production in low-permeability gas reservoirs, this study focuses on the strongly heterogeneous reservoirs in the central Linxing area of the Ordos Basin. Laboratory-scale physical simulation experiments of commingled production were conducted on core samples from the Shiqianfeng (Q5) and Shihezi (He4) formations, along with the No. 8 + 9 coal seam. The gas production behavior, including the evolution of flow rates, the occurrence of staggered production peaks, and the resulting interlayer interference coefficients, was systematically analyzed and compared between single-layer and multi-layer commingled production scenarios. Experimental results reveal a positive correlation between cumulative gas production and layer permeability under single-layer production conditions. Specifically, the high-permeability layer (0.6470 mD) yielded 65.22 mL, whereas the low-permeability layer (0.1061 mD) produced 36.51 mL, representing a 44.02% reduction relative to the former. Under commingled production conditions, the productivity of the low-permeability layer exhibited more severe inhibition, showing declines in instantaneous production of 34.02–48.96% and cumulative production of 15.50–20.61%. These reductions substantially exceed those observed in the high-permeability layer, which ranged from 6.14% to 6.35% and from 5.00% to 8.76%, respectively. Furthermore, a greater permeability contrast results in a more pronounced difference in gas breakthrough timing. For a permeability ratio of 3, the breakthrough time difference reaches 191 s, compared to 131 s for a ratio of 2. The interlayer interference coefficient exhibits a negative correlation with the permeability contrast. When the contrast is 3, the interference coefficient for the low-permeability layer reaches 79.39%, representing an 84.51% increase relative to the coefficient observed at a contrast of 2. This indicates that larger permeability contrasts lead to more severe interference effects on low-permeability layers. These findings provide theoretical support for optimizing the efficient development of multi-layer commingled production in low-permeability unconventional gas reservoirs, highlighting the necessity of incorporating permeability contrast analysis in commingled production design. Full article

To address interlayer interference during multi-layer commingled production in gas reservoirs with pressure differences, this study investigates the low-permeability gas reservoir in the central Linxing area of the Ordos Basin. High-temperature, high-pressure physical simulation experiments were conducted to systematically study single-layer, two-layer, and three-layer commingled production under different pressures (13, 15, and 17 MPa). A large-scale physical simulation system, capable of withstanding 100 °C and 50 MPa, was constructed for the dynamic monitoring of multi-layer commingled production. This system accurately characterized the instantaneous gas production, cumulative gas production, and pressure drop behavior of individual layers under both single-layer and commingled production conditions. The results indicate that significant interlayer interference occurs during multi-layer commingled production. This interference is primarily manifested as a capacity inhibition effect, where the high-pressure layer suppresses the production of the low-pressure layer. Typical phenomena accompanying this effect include ‘backflow’ and ‘staggered production peaks’. Quantitative analysis indicates that the cumulative gas production for two-layer and three-layer commingled production is 3.2% and 9.06% lower, respectively, than the summed production from equivalent single-layer operations. Notably, in the three-layer commingled production scenario, the productivity of the low-pressure layer (Q5) was reduced by 19.87%, a significantly greater loss compared to the 4.39% reduction observed in the high-pressure layer (T2). Furthermore, the study demonstrates that the severity of interlayer interference is positively correlated with the interlayer pressure difference. Additionally, as the number of commingled layers increases, the interference effect exhibits a superimposed enhancement characteristic. Full article

Deep coalbed methane (CBM) development faces significant challenges due to extreme geological conditions (high stress, elevated pressure, high temperature) that differ fundamentally from shallow reservoirs. Traditional productivity models developed for shallow CBM often fail to accurately predict deep reservoir performance. The complex “stress-desorption-flow” multi-field coupling mechanism, intensified under deep conditions, critically controls production dynamics but remains poorly understood. This study develops a multi-layer, commingled, coupled geomechanical-flow model for the Hujiertai deep CBM block (2140~2170 m) in Xinjiang, China. The model, integrating gas-water two-phase flow, Langmuir adsorption, and transient geostress evolution, was validated against field production data, achieving a low relative error of 1.2% in the simulated average daily gas rate. Results indicate that: (1) Geomechanical coupling is critical. The dynamic competition between effective stress compaction and matrix shrinkage limits fracture porosity reduction to ~2%, enabling a characteristic “rapid incline, 1–2-year plateau, gradual decline” production profile and significantly enhancing cumulative gas production. (2) Porosity (10~30%) is positively correlated with productivity: a 10-percentage-point increase raises the peak gas rate by 2.1% and cumulative production by 2.8%. Conversely, high initial cleat permeability boosts early rates but accelerates geomechanical damage (cleat closure), lowering long-term productivity. (3) Stimulation parameters show a trade-off. SRV only dictates short-term, near-wellbore production. Higher fracture permeability (peak rate +17% per 500 mD) boosts early output but accelerates depletion and stress-induced closure. The multi-field coupling mechanisms revealed and the robust model developed provide a theoretical basis for optimizing fracturing design and production strategies for analogous deep CBM plays. 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

To address the challenges of characterizing commingled production from multiple channel sand layers with varying boundaries and shapes in tight gas reservoirs, a novel Rate Transient Analysis (RTA) model was established based on the principle of equivalent seepage volume (ESV). This model enables the determination of boundary sizes and permeabilities of individual channel sand layers within commingled tight reservoirs using modern production decline analysis theory. The production decline behavior under different channel sizes, numbers, and configurations was systematically investigated through type curve analysis. The results reveal the existence of five distinct stages in the production decline curves for unequal-width channel sands. The intermediate transient flow stage serves as a diagnostic indicator for identifying boundary disparities among layers. Furthermore, reservoirs with smaller boundary distances, fewer wide channel sand layers, and lower thickness proportions of wider channels exhibit poorer productivity and tend to experience accelerated production decline during early and middle transient flow stages. The proposed method provides an effective approach for characterizing boundary parameters of commingled tight reservoirs and offers a theoretical foundation for evaluating individual layer contributions and productivity. Full article

Hydraulic fracturing technology significantly enhances reservoir conductivity by creating artificial fractures, serving as a crucial means for the economically viable development of low-permeability reservoirs. Accurate prediction of post-fracturing productivity is essential for optimizing fracturing parameter design and establishing scientific production strategies. However, current limitations in understanding post-fracturing production dynamics and the lack of efficient prediction methods severely constrain the evaluation of fracturing effectiveness and the adjustment of development plans. This study proposes a machine learning-based method for predicting post-fracturing productivity in multi-layer commingled production wells and validates its effectiveness using a key block from the PetroChina North China Huabei Oilfield Company. During the data preprocessing stage, the three-sigma rule, median absolute deviation, and density-based spatial clustering of applications with noise were employed to detect outliers, while missing values were imputed using the K-nearest neighbors method. Feature selection was performed using Pearson correlation coefficient and variance inflation factor, resulting in the identification of twelve key parameters as input features. The coefficient of determination served as the evaluation metric, and model hyperparameters were optimized using grid search combined with cross-validation. To address the multi-layer commingled production challenge, seven distinct datasets incorporating production parameters were constructed based on four geological parameter partitioning methods: thickness ratio, porosity–thickness product ratio, permeability–thickness product ratio, and porosity–permeability–thickness product ratio. Twelve machine learning models were then applied for training. Through comparative analysis, the most suitable productivity prediction model for the block was selected, and the block’s productivity patterns were revealed. The results show that after training with block-partitioned data, the accuracy of all models has improved; further stratigraphic subdivision based on block partitioning has led the models to reach peak performance. However, data volume is a critical limiting factor—for blocks with insufficient data, stratigraphic subdivision instead results in a decline in prediction performance. 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

With the development of tracer technology and the improvement of fine management in oil fields, chemical tracer monitoring is widely used to analyze the production profiles in commingled wells and horizontal wells. However, most existing tracer technologies can only determine the production profile and cannot calculate the water cut. This paper proposes an intelligent slow-release chemical tracer monitoring technology and a corresponding interpretation methodology, which can quantify the oil and water production rates and dynamically analyze the water cut of production profiles by simultaneous deployment of oil-soluble and water-soluble tracers. To validate this approach, this method was applied to well A of the Bohai Oilfield. The results showed that the calculation model based on produced tracer concentration can quantitatively determine the production profile and water cut of the monitored well. During the stable production period, Well A exhibited high production rates and a low water cut, and the contribution of oil production varied greatly among different layers. The first and third sections were identified as the main contributors, accounting for 51.8% and 23.2% of production, respectively, while the second and fourth sections showed lower contributions of 15.1% and 9.9%. The water cut of each section was below 30%. This intelligent slow-release tracer monitoring technology allowed for continuous production profiles in the monitored well. The proposed method provides effective guidance for characterizing the production profile and water flooding patterns of each layer. It is helpful for the efficient development of oil and gas reservoirs. Full article

During the development of multi-layer tight sandstone gas reservoirs in Ordos Basin, China, it has not been easy to calculate accurately the production of each individual layer in gas wells. However, production allocation provides a vital basis for evaluating dynamic reserves and drainage areas of gas wells and remaining gas distributions of gas layers. To improve the accuracy and reliability of production allocation of gas wells, a new model was constructed based on the seepage equation, material balance equation, and pipe string pressure equation. In particular, this new model introduced the seepage equation with an elliptical boundary to accurately capture the fluid flow characteristics within a lenticular tight gas reservoir. The new model can accurately calculate the production and reservoir pressure of each individual layer in gas wells. In addition, the new model was validated and applied in the Sulige gas field, Ordos Basin. The following conclusions were drawn: First, The gas production contribution rates of pay zones based on the new model are fairly close to the measurements of the production profile logging, with errors less than 10%. Second, The overall drainage area of a gas well lies among those of each pay zone, and the total dynamic reserves of the well are close to the sum of the dynamic reserves of pay zones. Third, Higher permeability may lead to higher initial gas production of the pay zone, but the ultimate gas production contributions of pay zones are affected jointly by permeability and dynamic reserves. Finally, The new model has been successfully applied to the SZ block of the Sulige gas field, in which the fine evaluation of dynamic reserves, drainage areas, gas production, recovery factors, and remaining gas distributions of different layers was delivered, and the application results provide technical support for the future well placement and enhanced gas recovery of the block. Full article

In this study, a practical and comprehensive experimental technique has been proposed to investigate the interlayer interference characteristics in multilayer tight sandstone gas reservoirs with multi-pressure systems and different reserves. Firstly, single-layer depletion simulation experiments were conducted to measure the gas flow rate and gas extraction efficiency for each of the six layers. A series of physical simulation experiments were then conducted to monitor gas production and pressure variations in commingled multilayer production scenarios under various conditions. Finally, interlayer interference characteristics and gas extraction efficiencies and the main controlling factors were evaluated, analyzed, and identified. The interlayer pressure differential is found to be the primary factor dictating both interference and gas production, followed by initial gas production rates, and permeability variations in the order of positive significance. A higher interlayer pressure differential, a lower initial gas production rate, and a larger permeability variation result in an increase in interlayer interference and a reduction in gas production during commingled production. Increasing the number of commingled layers leads to an overall increase in gas production losses of 10.95% for two layers to 13.35% for four layers. Layers exhibiting small interlayer pressure difference are positively compatible for commingled production. Full article