Search Results (52)

Characterizing multiscale fracture networks in shale gas reservoirs remains challenging, while the limited applicability of conventional continuum-based models and insufficient multi-objective coordination often lead to low efficiency in development optimization. To address these issues, this study proposes a production history matching and multi-objective collaborative optimization framework for shale gas horizontal wells based on an equivalent fractal fracture (EFF) model. By integrating fractal theory with intelligent optimization techniques, a multiscale equivalent fractal permeability tensor is constructed, forming a hybrid machine-learning framework that combines physics-based fractal constraints with data-driven learning for efficient representation of complex fracture networks. Microseismic event clouds were converted into continuous fracture-density and fractal-geometry descriptors through denoising, temporal alignment, and spatial interpolation, and these descriptors were mapped to the equivalent fractal fracture model to dynamically update key flow parameters for history matching and parameter inversion. On this basis, a multi-objective collaborative optimization strategy is developed to achieve simultaneous time-varying fracture characterization and dynamic regulation of development parameters. Comparative results indicate that the EFF-based approach yields a production prediction error of 6.8%, slightly higher than the 4.2% obtained using discrete fracture network (DFN) models, while requiring only one-eighteenth of the computational time. Using the net present value (NPV) as the unified objective function, constraints are imposed on bottom-hole flowing pressure, flowback rate and system switching time for optimization. With the optimized pressure drop being more uniform and the gas saturation distribution being more balanced, it is verified that “EFF + NPV” can achieve the coordinated optimization of “production capacity—decline—cost” and enhance the development efficiency. Full article

Production profiling is essential for optimizing production strategies in oil and gas wells. Conventional production logging tools provide only discrete, time-limited measurements and face operational challenges in long or complex horizontal wells. Distributed fiber-optic sensing (DTS/DAS) enables continuous, full-wellbore monitoring but each sensing modality has limitations when used alone: DTS interpretation is influenced by wellbore disturbances and thermal hysteresis, while DAS acoustic energy does not always correspond to actual inflow zones. This study proposes a joint interpretation method integrating DTS-based temperature inversion with DAS frequency-band energy and apparent velocity analysis. DTS data are processed using a coupled wellbore–formation heat-transfer model to obtain segmental flow rates, while DAS data are analyzed using short-time Fourier transform, cross-correlation, and Hough transform to extract positive and negative apparent velocities indicating fluid migration directions. Field results show that high-production intervals at 4126–4486 m correlate with positive apparent velocities, whereas medium-/low-production and shut-in stages exhibit persistent negative velocities linked to backflow and reinjection. The combined interpretation effectively distinguishes reservoir inflow from wellbore flow by jointly constraining thermal response and flow direction, thereby reducing uncertainties associated with single-method analysis. Full article

Shale oil reservoirs exhibit ultralow permeability and complex pore structures, which result in non-Darcy low-velocity flow and cause permeability to be stress-sensitive. Moreover, two-phase flow of oil and gas frequently occurs during the depletion of shale oil reservoirs. Consequently, investigating the rate-transient behavior of shale oil wells necessitates comprehensive consideration of multiphase flow, threshold pressure gradients, and stress sensitivity. Although numerous analytical models exist for rate-transient analysis of multistage fractured horizontal wells, none of them simultaneously incorporate these critical factors. In this study, we extend the classical five-region model to incorporate multiphase flow, threshold pressure gradients, and stress sensitivity. The proposed model is solved using Pedrosa’s transformation, perturbation theory, the Laplace transform, and the Stehfest numerical inversion method. A systematic analysis of the influence of various parameters on the oil production rate and cumulative oil production is conducted, and a field case study is presented to validate the applicability and effectiveness of the model. It is found that the permeability modulus of the main fracture, the half-length of the main fracture, and the threshold pressure gradient of the unstimulated reservoir have a significant influence on cumulative oil production spanning 20 years. With a 100% relative input error, these parameters result in prediction errors of 23.77%, 16.65%, and 17.78%, respectively. In contrast, the threshold pressure gradient of the main fracture and the threshold pressure gradient of the stimulated reservoir have a negligible impact; under the same level of input error (100%), they cause only 0.36% and 0.48% prediction errors in the 20-year cumulative oil production period, respectively. This research provides an efficient and reliable framework for analyzing production data and forecasting shale oil well performance. Full article

Natural fractures in tight sandstone reservoirs are the key factors controlling hydrocarbon flow and productivity. The Bozi-1 gas reservoir in the Kuqa Depression, as a typical ultra-deep tight sandstone gas reservoir, is characterized by low-porosity and ultra-low-permeability sandstones. This study addresses the limitations of previous fracture characterization, which primarily focused on macro-structural fractures while neglecting medium- and small-scale fractures. We integrate multi-source heterogeneous data, including core, well-logging imaging, seismic, and production observations, to systematically conduct multi-scale natural fracture characterization and modeling. First, the overall geology of the study area is briefly introduced, followed by a detailed description of the development characteristics of large-scale and medium–small-scale fractures, achieving a multi-scale representation of complex curved fracture networks. Finally, the three-dimensional multi-scale fracture model is validated using static indicators, including production characteristics, water invasion features, and well leakage data. The main findings are as follows: (1) Large-scale fractures in the Bozi-1 reservoir are mainly oriented near EW, NE–SW, and NW–SE, acting as the primary hydrocarbon migration pathways. Medium–small-scale fractures predominantly develop near SN, NE–SW, NW–SE, and near EW directions, exhibiting strong heterogeneity. (2) The complex curvature of large-scale fractures was captured by the “adaptive sampling + segmented splicing + equivalent distribution of fracture flow capacity” method, while the distribution of effective medium–small-scale fractures across the study area was represented using “single-well Stoneley wave inversion + seismic machine learning prediction”, achieving an 86% match with actual single-well measurements. (3) Model reliability was further verified through static comparisons, including production characteristics (unimpeded flow vs. effective fracture density, R² = 0.92), water invasion features (fracture-dominated water invasion matching fracture distribution), and well leakage characteristics (matching rate of high fracture density zones: 84.2%). The results provide key technical support for the precise characterization of fracture systems and establish a model ready for dynamic simulation in ultra-deep tight sandstone gas reservoirs. Full article

This study presents a CO₂ injectivity analysis for the depleted gas field Z offshore Malaysia using nodal analysis and sensitivity analysis. Reservoir permeability was estimated from the appraisal well DST report, which recorded an absolute open flow (AOF) of 253 MMscfd, and sensitivity analyses were conducted for injection pressure, tubing diameter, reservoir pressure, permeability, and thickness. The base-case nodal analysis resulted in an optimal CO₂ injection rate of 52.3 MMscfd. Injection pressure, permeability, and thickness were linearly proportional to injection rate, whereas reservoir pressure showed an inverse relationship. The analysis of injection rate per tubing diameter indicated that 4.548-inch tubing, with 15.11 MMscfd per inch, provided the highest efficiency. A total CO₂ injection volume of 5 Tcf was distributed among five wells, and four injection period scenarios (20, 15, 10, 5 years) were designed based on flow efficiency. In the 5-year scenario, the bottomhole pressure of all wells exceeded the formation parting pressure at a reservoir pressure of approximately 1000 psia, indicating that the target injection rate of 2739 MMscfd could not be achieved. Tubing injectivity index (TII) analysis showed that higher TII values represented greater injection efficiency from a vertical flow perspective. Full article

Downhole kick is one of the most severe safety hazards in deep and ultra-deep well drilling operations. Traditional monitoring methods, which rely on surface flow rate and fluid level changes, are limited by their delayed response and insufficient sensitivity, making them inadequate for early warning. This study proposes a real-time monitoring technique for gas content in drilling fluid based on the attenuation principle of Ba-133 γ-rays. By integrating laboratory static/dynamic experiments and Geant4-11.2 Monte Carlo simulations, the influence mechanism of gas–liquid two-phase media on γ-ray transmission characteristics is systematically elucidated. Firstly, through a comparative analysis of radioactive source parameters such as Am-241 and Cs-137, Ba-133 (main peak at 356 keV, half-life of 10.6 years) is identified as the optimal downhole nuclear measurement source based on a comparative analysis of penetration capability, detection efficiency, and regulatory compliance. Compared to alternative sources, Ba-133 provides an optimal energy range for detecting drilling fluid density variations, while also meeting exemption activity limits (1 × 10⁶ Bq) for field deployment. Subsequently, an experimental setup with drilling fluids of varying densities (1.2–1.8 g/cm³) is constructed to quantify the inverse square attenuation relationship between source-to-detector distance and counting rate, and to acquire counting data over the full gas content range (0–100%). The Monte Carlo simulation results exhibit a mean relative error of 5.01% compared to the experimental data, validating the physical correctness of the model. On this basis, a nonlinear inversion model coupling a first-order density term with a cubic gas content term is proposed, achieving a mean absolute percentage error of 2.3% across the full range and R² = 0.999. Geant4-based simulation validation demonstrates that this technique can achieve a measurement accuracy of ±2.5% for gas content within the range of 0–100% (at a 95% confidence interval). The anticipated field accuracy of ±5% is estimated by accounting for additional uncertainties due to temperature effects, vibration, and mud composition variations under downhole conditions, significantly outperforming current surface monitoring methods. This enables the high-frequency, high-precision early detection of kick events during the shut-in period. The present study provides both theoretical and technical support for the engineering application of nuclear measurement techniques in well control safety. Full article

Gas–water two-phase flow in horizontal and inclined wells is significantly influenced by gravitational forces and spatial asymmetry around the wellbore, resulting in complex and variable flow patterns. Accurate measurement of water holdup is essential for analyzing phase distribution and understanding multiphase flow behavior. Water holdup imaging provides a valuable means for visualizing the spatial distribution and proportion of gas and water phases within the wellbore. In this study, air and tap water were used to simulate downhole gas and formation water, respectively. An array capacitance arraay tool (CAT) was employed to measure water holdup under varying total flow rates and water cuts in a horizontal well experimental setup. A total of 228 datasets were collected, and the measurements were processed in MATLAB (2020 version) using three interpolation algorithms: simple linear interpolation, inverse distance interpolation, and Lagrangian nonlinear interpolation. Water holdup across the wellbore cross-section was also calculated using arithmetic averaging and integration methods. The results obtained from the three imaging algorithms were compared with these reference values to evaluate accuracy and visualize imaging performance. The CAT demonstrated reliable measurement capabilities under low- to medium-flow conditions, accurately capturing fluid distribution. For stratified flow regimes, the linear interpolation algorithm provided the clearest depiction of the gas–water interface. Under low- to medium-flow rates with high water content, both inverse distance and Lagrangian methods produced more refined images of phase distribution. In dispersed flow conditions, the Lagrangian nonlinear interpolation algorithm delivered the highest accuracy, effectively capturing subtle variations within the complex flow field. Full article

This paper considers the problem of estimating the quantitative parameters of a two-phase fluid flow in a well based on the dynamic physical flow model. This is a challenging problem in the oil and gas industry, where the knowledge of multiphase production rates plays an important role during reservoir characterization, production optimization and reservoir management. As the direct measurement of these rates is not easily available, they can be inferred from conventional sensors (e.g., pressure gauges) in combination with a dynamic multiphase flow model. The methodology proposed in this work uses inverse modeling concepts to estimate flow rates that are not measured directly. The mismatch between the available data and model prediction is numerically minimized, leading to the optimal set of dynamic flow variables characterizing the flow. Two different scenarios are considered: firstly, when the well has only a flow meter located at the wellhead (minimum amount of available information), and when the well has distributed pressure sensors in addition to the topside flow meter (maximum amount of information). The feasibility of the proposed concept is assessed via several simulation-based case studies. Full article

Deep coalbed methane wells often encounter challenges such as inefficient sand transport and sand accumulation in the horizontal sections during drainage, which significantly impact the stability of gas production and the efficiency of the gas lift system. To investigate the sand-carrying mechanisms in the horizontal sections of deep coalbed methane wells, this study develops a theoretical model for critical sand-carrying velocity based on gravitational, buoyant, drag, and pressure gradient forces. Additionally, a visualized experimental system was constructed using a multiphase pipe flow platform. By varying parameters such as liquid flow rate, gas–liquid ratio, gravel particle size, and pipe inclination, the critical conditions for sand transport were examined, and the dominant factors influencing sand transport in horizontal wellbore sections were identified. The experimental results indicate that water flow rate and particle size are inversely correlated with the gas volume required for sand transport, whereas inclination angle is positively correlated. The proposed model was validated against experimental data, showing a prediction error within 15%, thereby confirming its accuracy and engineering applicability. These findings offer theoretical guidance and technical references for efficient drainage and stable gas production in horizontal wellbore sections of deep coalbed methane wells. Full article

As a cost-effective transitional strategy, the integrated utilization and transportation of hydrogen and natural gas have gained significant attention as a viable pathway toward carbon neutrality. However, hydrogen’s low density, viscosity, and calorific value cause upward migration and accumulation in pipelines, raising embrittlement risks. Its high diffusion and leakage rates also pose significant safety challenges. To address hydrogen–natural gas blending challenges, achieving uniform mixing is crucial. This study systematically examines hydrogen–methane mixing in T-junction pipelines via numerical simulations, analyzing hydrogen mixing ratios (HMR: 10–25%) and methane flow rates (4–10 m/s) to assess flow and mixing dynamics. The coefficient of variation (COV) quantifies mixing uniformity with spatial and temporal analyses, optimizing hydrogen injection for rapid, homogeneous mixing. The key findings are as follows: (1) The uniform mixing length (the minimum axial distance required for the first pipeline cross-section to achieve 95% mixing uniformity) decreases inversely with the HMR, from 100 D to 20.875 D (D represents the pipeline diameter) as the HMR rises from 10% to 25%. (2) Analysis of initial uniform mixing time (defined as the duration required for the first pipeline cross-section to achieve 95% mixing uniformity) shows significant reduction with increasing HMR. While methane flow rate has a less pronounced effect, it nevertheless contributes to reducing the outlet uniform mixing time (defined as the time required to attain 95% mixing uniformity at the pipeline outlet). (3) A fundamental trade-off in engineering applications is established: increasing the HMR reduces mixing length but extends overall mixing time (difference between outlet and initial mixing times), while higher methane flow rates shorten overall mixing time at the cost of increased mixing length. The primary objective of this research is to elucidate the fundamental fluid dynamics of hydrogen–methane mixtures in T-junction pipelines, providing scientific insights for the safe and efficient operation of hydrogen-blended natural gas pipeline systems. Full article

To promote energy conservation and a low-carbon approach in natural gas storage, efficient methods for utilizing waste heat during gas injection and maintaining adequate cooling rates are crucial. This study developed a three-dimensional model integrating the desorption process of hydrated salts to analyze temperature and flow fields within a moving bed during heat exchange. This study systematically evaluated the effects of operating parameters on key outcomes, including the outlet temperatures of hydrated salts and natural gas, as well as the waste heat recovery ratio. Results indicated that the outlet temperatures of natural gas and particles varied synchronously, while the waste heat recovery ratio exhibited an inverse relationship with the natural gas outlet temperature. Remarkably, incorporating a composite material comprising hydrated calcium chloride and hydrated magnesium sulfate into the moving bed reduced the natural gas outlet temperature from 60 °C to 47.5 °C. Concurrently, the waste heat recovery ratio improved substantially, rising from 66% to 90%. Furthermore, the proposed moving bed heat exchange system requires less than one-third of the volume of conventional natural gas air-cooled heat exchangers. These findings provide theoretical insights and robust data support for enhancing cross-seasonal waste heat utilization in natural gas storage facilities. Full article

Forest disturbance is one of the main drivers of forest carbon flux change. How to accurately estimate the carbon flux caused by forest disturbance is an important research problem. In a previous study, the authors proposed a Grid-based Carbon Accounting (GCA) model that used remote sensing data to estimate forest carbon fluxes in North Carolina from 1986 to 2010. However, the original model was unable to track legacy emissions from previously harvested wood products and was unable to consider forest growth conditions before and after forest disturbance. This paper made some improvements to the original GCA model to enable it to track fluxes between all major aboveground live carbon pools, including pre-disturbance growth and growth of undisturbed forests, which were not included in the initial model. Based on existing timber product output (TPO) survey data and annual TPO records inversed from remote sensing data, we also worked to clarify the distribution ratios of removed C between slash and different wood product pools. Specifically, the average slash ratio for North Carolina was calculated from the difference between the C removed and the C flowing into the wood product as calculated from TPO survey data. County- and year-specific ratios were then calculated using the annual TPO records obtained from remote sensing and TPO survey data, dividing the removed remaining C into pools P1, P10, and P100, which were then applied to each 30 m pixel based on the county and year to which the pixel belonged. After compensating for these missing legacy emissions and adjusting forest growth rates from Forest Inventory and Analysis (FIA) data, we estimated a net carbon sink of 218.1 Tg of the flux associated with live aboveground biomass and harvested wood products from North Carolina woodlands over the 25-year study period (1986–2010). This estimate is close to the greenhouse gas emission and sink data provided by the U.S. Department of Agriculture for North Carolina and is comparable to estimates reported by several other studies. Full article

Composite polymer membranes were obtained using the so-called dry phase inversion and were used for desalination of diluted saline water solutions by pervaporation (PV) method. The tests used a two-layer backing, porous, ultrafiltration commercial membrane (PS20), which consisted of a supporting polyester layer and an active polysulfone layer. The active layer of PV membranes was obtained in an aqueous environment, in the presence of a surfactant, by cross-linking a 5 wt.% aqueous solution of polyvinyl alcohol (PVA)—using various amounts of cross-linking substances: 50 wt.% aqueous solutions of glutaraldehyde (GA) or citric acid (CA) or a 40 wt.% aqueous solution of glyoxal. An ethylene glycol oligomer (PEG 200) was also used to prepare active layers on PV membranes. Witch its help a chemically cross-linked hydrogel with PVA and cross-linking reagents (CA or GA) was formed and used as an active layer. The manufactured PV membranes (PVA/PSf/PES) were used in the desalination of water with a salinity of 35‰, which corresponds to the average salinity of oceans. The pervaporation method was used to examine the efficiency (productivity and selectivity) of the desalination process. The PV was carried at a temperature of 60 °C and a feed flow rate of 60 dm³/h while the membrane area was 0.005 m². The following characteristic parameters of the membranes were determined: thickness, hydrophilicity (based on contact angle measurements), density, degree of swelling and cross-linking density and compared with the analogous properties of the initial PS20 backing membrane. The physical microstructure of the cross-section of the membranes was analyzed using scanning electron microscopy (SEM) method. Full article

Proteins form the fastest-growing therapeutic class. Due to their intrinsic instability, loss of native structure is common. Structure alteration must be carefully evaluated as structural changes may jeopardize the efficiency and safety of the protein-based drugs. Hydrogen deuterium exchange (HDX) has long been used to evaluate protein structure and dynamics. The rate of exchange constitutes a sensitive marker of the conformational state of the protein and of its stability. It is often monitored by mass spectrometry. Fourier transform infrared (FTIR) spectroscopy is another method with very promising capabilities. Combining protein microarrays with FTIR imaging resulted in high throughput HDX FTIR measurements. BaF₂ slides bearing the protein microarrays were covered by another slide separated by a spacer, allowing us to flush the cell continuously with a flow of N₂ gas saturated with ²H₂O. Exchange occurred simultaneously for all proteins and single images covering ca. 96 spots of proteins that could be recorded on-line at selected time points. Each protein spot contained ca. 5 ng protein, and the entire array covered 2.5 × 2.5 mm². Furthermore, HDX could be monitored in real time, and the experiment was therefore not subject to back-exchange problems. Analysis of HDX curves by inverse Laplace transform and by fitting exponential curves indicated that quantitative comparison of the samples is feasible. The paper also demonstrates how the whole process of analysis can be automatized to yield fast analyses. Full article

Hydraulic fracturing is extensively utilized for the prevention and control of gas outbursts and rockbursts in the deep sections of coal mines. The determination of fracturing construction parameters based on the coal seam conditions and stress environments merits further investigation. This paper constructs a damage analysis model for coal under hydraulic loads, factoring in the influence of the intermediate principal stress, grounded in the octahedron strength theory analysis approach. It deduces the theoretical analytical equation for the damage distribution of a coal medium subjected to small-flow-rate hydraulic fracturing in underground coal mines. Laboratory experiments yielded the mechanical parameters of coal in the study area and facilitated the fitting of the intermediate principal stress coefficient. Leveraging these datasets, the study probes into the interaction between hydraulic loads and damage radius under assorted influence ranges, porosity, far-field crustal stresses, and brittle damage coefficients. The findings underscore that hydraulic load escalates exponentially with the damage radius. Within the variable range of geological conditions in the test area, the effects of varying influence range, porosity level, far-field stress, and brittle damage coefficient on the outcomes intensify one by one; a larger hydraulic load diminishes the impact of far-field stress variations on the damage radius, inversely to the influence range, porosity, and brittle damage. The damage radius derived through the gas pressure reduction method in field applications corroborates the theoretical calculations, affirming the precision of the theoretical model. These findings render pivotal guidance for the design and efficacy assessment of small-scale hydraulic fracturing in underground coal mines. Full article