Search Results (20)

This work is focused on developing a computational model to predict the production rate and pressure evolution of natural gas from unconventional reservoirs, particularly shale gas deposits. The model is based on the principle of conservation of mechanical energy and was developed from the transient solution of Bernoulli’s equation. This solution was obtained by computing the pressure evolution in the well resulting from the combined action of extracting the free gas and of gasification from kerogen. The transient behavior of gas production by hydraulic fracturing was calculated by numerically integrating Bernoulli’s equation. The curves representing gas flow evolution were considered as a series of stepwise steady states under a constant gas flow rate, similar to the pressure–time curves. These time steps were connected by instantaneous drops in pressure or gas flow rates. On the other hand, the delayed release of the adsorbed and dissolved gas in the kerogen was accurately calculated by introducing a semi-empirical gas pressure source term into the gas well pressure equation. The effect of this source is to gradually increase the gas pressure in the reservoir, emulating the gas release mechanisms from the organic matter. Model validation was based on production data from the unconventional reservoirs Eagle Ford, U.S.A., and Burgos basin, México. The initial measured gas production rate was used to determine a global friction factor of the gas flowing out from soil cracks and ducts. Additionally, measured production rate data were used to determine the coefficients of the source term function. Pearson correlation coefficients of 0.97 and 0.96 were obtained for Eagle Ford and Burgos basins data, respectively. In contrast, the corresponding coefficients calculated from the traditional Arps’ model were 0.89 and 0.5, respectively. The present pressure source model (PSM) represents a new approach to characterize the process of gas production from unconventional reservoirs, proving to be accurate in forecasting both the gas flow rate and pressure evolution during gas production. The postulated pressure source term was shown to mimic the desorption and diffusion kinetics, which release free gas from the kerogen. Full article

Multi-stage hydraulic fracturing (MsHF) is the main technology to improve hydrocarbon recovery from shale plays. Associated with their rich organic contents and laminated depositional environments, shales exhibit transverse isotropic (TI) characteristics. In several cases, the lamination planes are horizontal in shale formations with a symmetric axis that are vertical to the bedding plane; hence, shale formations are known as transverse isotropic vertical (TIV) rocks. Ignoring the TIV nature of shale formations leads to erroneous estimates of in situ stresses and consequently to inefficient designs of fractural geometry, which negatively affects the ultimate recovery. The goal of this study is to investigate the effects of TIV medium characteristics on fractural geometry, spacing, and stress shadow development in the Jurassic Tuwaiq Mountain formation (TMF) in the Jafurah basin, which is a potential unconventional world-class play. This formation is the main source for prolific Jurassic oil reservoirs in Saudi Arabia. On the basis of a petrophysical evaluation in the Jafurah basin, TMF exhibited exceptional unconventional gas characteristics, such as high total organic content (TOC) and low clay content, and it was in the proper maturity window for oil and gas generation. The unconventional Jafurah field covers a large area that is comparable to the size of the Eagle Ford shale play in South Texas, and it is planned for development through multi-stage hydraulic fracturing technology. In this study, analytical modeling was performed to estimate the fractural geometry and in situ stresses in the anisotropic medium. The results show that the Young’s modulus anisotropy had a noticeable impact on fractural width, whereas the impact of Poisson’s ratio was minimal. Moreover, we investigated the impact of stress anisotropy and other rock properties on the stress shadow, and found that a large stress anisotropy could result in fractures being positioned close to one another or theoretically without minimal fractural spacing concerns. Additionally, we estimated the fractural aspect ratio in different propagation regimes and observed that the highest aspect ratio had occurred in the fractural toughness-dominated regime. This study also compares the elastic properties and confirms that TMF exhibited greater anisotropic properties than those of Eagle Ford. These findings have practical implications for field operations, particularly with regard to the fractural geometry and proppant placement. Full article

Shale oil and gas production areas are especially active in Texas. The Eagle Ford Shale in south central Texas contributes substantially to US oil and gas production; it has repeatedly been the focus of air quality studies due to its associated emissions. Among these emissions are hazardous air pollutants such as benzene, a known carcinogen. To monitor exposure to such compounds, we teamed up with local citizens in 2019 to begin a passive sampling study for hydrocarbons. The study tracked selected non-methane hydrocarbons at six locations throughout a busy central production area of the shale. A state air quality monitoring station allowed for a comparison exercise, and we report both the results of that exercise and the observations from various properties affected by the surrounding oil and gas exploration activities. The passive samplers accurately reflected mean to median ambient hydrocarbon levels despite high variability and skewness in the hourly measurements. Field sites either right next to oil and gas production pads, surrounded by more surface pads than other sites, or affected by an additional emission source showed higher exposure to selected hydrocarbons. Passive sampling shows promise to bridge the gap between centralized air monitoring and campaign-style mobile monitoring to evaluate hydrocarbon emissions and abundances. It is a cost-effective way to provide both spatial and temporal information on exposure levels. Full article

Safe drilling and effective fracturing are constant challenges for shale formations. One of the most important influencing factors is the accurate characterization of the deformation and damage caused by inherent lamination and natural fractures. Furthermore, shale formations exhibit fine-scale heterogeneity, which conventional laboratory methods (linear variable differential transformer (LVDT), strain gauges, etc.) cannot distinguish. To overcome these constraints, this research aims to investigate the damage and deformation characteristics of shale samples using three-dimensional digital image correlation (3D-DIC). Under uniaxial and diametrical compression, samples of Wolfcamp, Mancos, and Eagle Ford shale with distinct lamination and natural fractures are evaluated. The 3D-DIC system is utilized for image processing, visualization, and analysis of the shale damage process under varying loads. DIC made quantitative full-field strain maps with load (tension, compression, and shear), showing all the damage process steps and strain localization zones (SLZs). DIC maps are used to quantify damage variables in order to investigate sample damage. Damage variables are used to categorize the damage evolution process of shale specimens into four stages: initial damage, linear elastic, elastic–plastic, and plastic damage. Characterizing shale damage evolution with a strain localization line is more effective because there is more damage there than in the whole sample. Damage variables based on major strain and its standard deviation from the DIC strain map for all tested shale samples follow a similar trend, though diametrical compression variables are greater than uniaxial compression. In both uniaxial and diametrical compression, the Wolfcamp shale was reported to have the highest damage variable, which was measured at 0.37, while the Eagle Ford shale was reported to have the lowest damage variable. This image-based technique is more effective not only for understanding the laminated and naturally fractured rocks but also for predicting the hydraulic fractures that will occur during the stimulation process. Full article

Gas adsorption in the porous shale matrix is critical for gas-in-place (GIP) evaluation and exploration. Adsorption investigations benefit significantly from the use of molecular simulation. However, modelling adsorption in a realistic shale topology remains a constraint, and there is a need to study the adsorption behaviour using molecular models containing both organic and inorganic nanopores. Most simulations use a single component, either kerogen (organic composition) and quartz or clay (inorganic composition), to represent the shale surface. In this work, the molecular dynamic (MD) and grand conical Monte Carlo (GCMC) simulations were utilised to provide insight into methane adsorption behaviour. Amorphous shale structures composed of kerogen and quartz were constructed. The kerogen content was varied to replicate the shale with 2 wt.% and 5 wt.% Total Organic Carbon (TOC) content with 5 nm pore size. The simulated densities of the shale structures showed consistent values with actual shale from the Montney, Antrim, and Eagle Ford formations, with 2.52 g/cm³ and 2.44 g/cm^3, respectively. The Average Error Analysis (ARE) was used to assess the applicability of the proposed amorphous shale model to replicate the laboratory adsorption isotherm measurements of actual shale. The ARE function showed that the amorphous shale shows good agreement with experimental measurements of all Barnett shale samples with an average of 5.0% error and slightly higher for the Haynesville samples with 8.0% error. The differences between the experimental adsorption measurement and simulation resulted from the amorphous packing, and actual shales have more minerals than the simulated model. Full article

Linear fracturing fluid (LFF) provides viscosity driven benefits of proppant suspensibility and fluid loss control, and with the use of a breaker agent, flowback recovery can be greatly enhanced. Shale tensile strength is critical in the prediction of fracture initiation and propagation, but its behavior under the interaction with LFF at reservoir temperature conditions remains poorly understood. This necessitated an in-depth investigation into the tensile strengths of Eagle Ford and Wolfcamp shales under thermally conditioned LFF and reservoir temperature controlled conditions. Brazilian Indirect Tensile Strength (BITS) testing was carried out for the quantitative evaluation of shale tensile strength, followed by extensive failure pattern classifications and surface crack length analysis. The thermally conditioned LFF saturation of shale samples led to average tensile strength (ATS) increases ranging from 26.33–51.33% for Wolfcamp. Then, for the Eagle Ford samples, ATS increases of 3.94 and 6.79% and decreases of 3.13 and 15.35% were recorded. The exposure of the samples to the temperature condition of 90 °C resulted in ATS increases of 24.46 and 33.78% for Eagle Ford and Wolfcamp shales, respectively. Then, for samples exposed to 220 °C, ATS decreases of 6.11 and 5.32% were respectively recorded for Eagle Ford and Wolfcamp shales. The experimental results of this research will facilitate models’ development towards tensile strength predictions and failure pattern analysis and quantifications in the LFF driven hydraulic fracturing of shale gas reservoirs. Full article

Shale oil/gas extraction has expanded rapidly in the last two decades due to the rising energy prices and the advancement of technologies. Its development can have huge impacts on and, at the same time, is also deeply affected by energy markets, especially in an era with high economic uncertainty. Understanding and monitoring shale oil/gas development over large regions are critical for both energy policies and environmental protection. However, there are currently no applicable methods to track the spatio-temporal dynamics of shale oil/gas development. To fill this gap, we propose a new NDVI Trajectroy Matching algorithm to track shale oil/gas development using the annual Landsat NDVI composite time series from 2000 to 2020. The results reveal that our algorithm can accurately extract the location and time of shale oil/gas exploitation in Eagle Ford and Three Forks, with an accuracy of 83.80% and 81.40%, respectively. In the Eagle Ford area, accuracy for all disturbance year detection was greater than 66.67%, with the best in 2011 and 2019 at 90.00%. The lowest accuracy in the Three Forks area was 63.33% in 2002, while the highest accuracy was 93.33% in 2019. In conclusion, the algorithm can effectively track shale oil/gas development with considerable accuracy and simplicity. We believe that the algorithm has enormous potential for other applications, such as built-up regions, forests, farmlands, and water body expansion and contraction involving vegetation damage. Full article

The recent decade’s rapid unconventional oil and gas development in the Eagle Ford of south-central Texas has caused increased hydrocarbon emissions, which we have previously analyzed using data from a Texas Commission on Environmental Quality air quality monitoring station located downwind of the shale area. Here, we expand our previous top-down emissions estimate and compare it to an estimated regional emissions maximum based on (i) individual facility permits for volatile organic compound (VOC) emissions, (ii) reported point source emissions of VOCs, (iii) traffic-related emissions, and (iv) upset emissions. This largely permit-based emissions estimate accounted, on average, for 86% of the median calculated emissions of C₃-C₆-hydrocarbons at the monitor. Since the measurement-based emissions encompass a smaller section of the shale than the calculated maximum permitted emissions, this strongly suggests that the actual emissions from oil and gas operations in this part of the Eagle Ford exceeded their permitted allowance. Possible explanations for the discrepancy include emissions from abandoned wells and high volumes of venting versus flaring. Using other recent observations, such as large fractions of unlit flares in the Permian shale basin, we suggest that the excessive venting of raw gas is a likely explanation. States such as Texas with significant oil gas production will need to require better accounting of emissions if they are to move towards a more sustainable energy economy. Full article

This study provides the engineering science underpinnings for improved characterization and quantification of the interplay of gases with kerogen and minerals in shale. Natural nanoporous media such as shale (i.e., mudstone) often present with low permeability and dual porosity, making them difficult to characterize given the complex structural and chemical features across multiple scales. These structures give nanoporous solids a large surface area for gas to sorb. In oil and gas applications, full understanding of these media and their sorption characteristics are critical for evaluating gas reserves, flow, and storage for enhanced recovery and CO${}_2$ sequestration potential. Other applications include CO${}_2$ capture from industrial plants, hydrogen storage on sorbent surfaces, and heterogeneous catalysis in ammonia synthesis. Therefore, high-resolution experimental procedures are demanded to better understand the gas–solid behavior. In this study, CT imaging was applied on the sub-millimeter scale to shale samples (Eagle Ford and Wolfcamp) to improve quantitative agreement between CT-derived and pulse decay (mass balance) derived results. Improved CT imaging formulations are presented that better match mass balance results, highlighting the significance of gas sorption in complex nanoporous media. The proposed CT routine implemented on the Eagle Ford sample demonstrated a 17% error reduction (22% to 5%) when compared to the conventional CT procedure. These observations are consistent in the Wolfcamp sample, emphasizing the reliability of this technique for broader implementation of digital adsorption studies in nanoporous geomaterials. Full article

Shale formations are attractive prospects due to their potential in oil and gas production. Some of the largest shale formations in the mainland US, such as the Tuscaloosa Marine Shale (TMS), have reserves estimated to be around 7 billion barrels. Despite their huge potential, shale formations present major concerns for drilling operators. These prospects have unique challenges because of all their alteration and incompatibility issues with drilling and completion fluids. Most shale formations undergo numerous chemical and physical alterations, making their interaction with the drilling and completion fluid systems very complex to understand. In this study, a high-pressure, high-temperature (HPHT) drilling simulator was used to mimic real time drilling operations to investigate the performance of inhibitive drilling fluid systems in two major shale formations (Eagle Ford Shale and Tuscaloosa Marine Shale). A series of drilling experiments using the drilling simulator and clay swelling tests were conducted to evaluate the drilling performance of the KCl drilling fluid and cesium formate brine systems and their effectiveness in minimizing drilling concerns. Cylindrical cores were used to mimic vertical wellbores. It was found that the inhibitive muds systems (KCl and cesium formate) provided improved drilling performance compared to conventional fluid systems. Among the inhibitive systems, the cesium formate brine showed the best drilling performances due to its low swelling rate and improved drilling performance. Full article

This paper advances a practical tool for production forecasting, using a 2-segment Decline Curve Analysis (DCA) method, based on an analytical flow-cell model for multi-stage fractured shale wells. The flow-cell model uses a type well and can forecast the production rate and estimated ultimate recovery (EUR) of newly planned wells, accounting for changes in completion design (fracture spacing, height, half-length), total well length, and well spacing. The basic equations for the flow-cell model have been derived in two earlier papers, the first one dedicated to well forecasts with fracture down-spacing, the second one to well performance forecasts when inter-well spacing changes (and for wells drilled at different times, to account for parent-child well interaction). The present paper provides a practical workflow, introduces correction parameters to account for acreage quality and fracture treatment quality. Further adjustments to the flow-cell model based 2-segment DCA method are made after history matching field data and numerical reservoir simulations, which indicate that terminal decline is not exponential (b = 0) but hyperbolic (with 0 < b< 1). The timing for the onset of boundary dominated flow was also better constrained, using inputs from a reservoir simulator. The new 2-segment DCA method is applied to real field data from the Eagle Ford Formation. Among the major insights of our analyses are: (1) fracture down-spacing does not increase the long-term EUR, and (2) fracture down-spacing of real wells does not result in the rate increases predicted by either the flow-cell model based 2-segment DCA (or its matching reservoir simulations) with the assumed perfect fractures in the down-spaced well models. Our conclusion is that real wells with down-spaced fracture clusters, involving up to 5000 perforations, are unlikely to develop successful hydraulic fractures from each cluster. The fracture treatment quality factor (TQF) or failure rate (1-TQF) can be estimated by comparing the actual well performance with the well forecast based on the ideal well model (albeit flow-cell model or reservoir model, both history-matched on the type curve). Full article

The United States has experienced exceptional growth in oil production via unconventional extraction for over a decade. This boom has led to an increase in hydrocarbon emissions to the atmosphere. With Texas as the leading contributor to growing oil production, it is important to assess the effects the boom has had on the environment and communities at local and regional levels. We conducted a pilot study to investigate the use of passive samplers for evaluating potential off-site risk from hydrocarbon emissions in a relatively low production activity area of the Texas Eagle Ford shale. Emissions from production sites include benzene, a hazardous air pollutant and known carcinogen. Passive hydrocarbon sampling devices (Radiello samplers) were used to monitor hydrocarbon levels on a rural property near a production site with an occasional flare for one year. Selected hydrocarbons were analyzed using thermal desorption and gas chromatography with flame ionization detection. Benzene concentrations were found to be correlated with changes in season, with higher abundance in the winter months. Benzene levels at this site were similar or higher than those observed in urban areas, away from shale oil and gas production. Increased benzene concentrations were distinguished when winds advected hydrocarbons from the production site, suggesting that oil and gas site emissions have a greater impact on the local community when winds advect them towards those living downwind; however, hydrocarbon levels in this low production area never exceeded state air monitoring comparison standards. Full article

Due to the rapid development of shale gas, a system has been established that can utilize a considerable amount of data using the database system. As a result, many studies using various machine learning techniques were carried out to predict the productivity of shale gas reservoirs. In this study, a comprehensive analysis is performed for a machine learning method based on data-driven approaches that evaluates productivity for shale gas wells by using various parameters such as hydraulic fracturing and well completion in Eagle Ford shale gas field. Two techniques are used to improve the performance of the productivity prediction machine learning model developed in this study. First, the optimal input variables were selected by using the variables importance method (VIM). Second, cluster analysis was used to analyze the similarities in the datasets and recreate the machine learning models for each cluster to compare the training and test results. To predict productivity, we used random forest (RF), gradient boosting tree (GBM), and support vector machine (SVM) supervised learning models. Compared to other supervised learning models, RF, which is applied with the VIM, has the best prediction performance. The retraining model through cluster analysis has excellent predictive performance. The developed model and prediction workflow are considered useful for reservoir engineers planning of field development plan. Full article

The production of shale gas and oil is associated with the generation of substantial amounts of wastewater. With the growing emphasis on sustainable development, the energy sector has been intensifying efforts to manage water resources while diversifying the energy portfolio used in treating wastewater to include fossil and renewable energy. The nexus of water and energy introduces complexity in the optimization of the water management systems. Furthermore, the uncertainty in the data for energy (e.g., solar intensity) and cost (e.g., price fluctuation) introduce additional complexities. The objective of this work is to develop a novel framework for the optimizing wastewater treatment and water-management systems in shale gas production while incorporating fossil and solar energy and accounting for uncertainties. Solar energy is utilized via collection, recovery, storage, and dispatch of heat. Heat integration with an adjacent industrial facility is considered. Additionally, electric power production is intended to supply a reverse osmosis (RO) plant and the local electric grid. The optimization problem is formulated as a multi-scenario mixed integer non-linear programming (MINLP) problem that is a deterministic equivalent of a two-stage stochastic programming model for handling uncertainty in operational conditions through a finite set of scenarios. The results show the capability of the system to address water-energy nexus problems in shale gas production based on the system’s economic and environmental merits. A case study for Eagle Ford Basin in Texas is solved by enabling effective water treatment and energy management strategies to attain the maximum annual profit of the entire system while achieving minimum environmental impact. Full article

The expansion of unconventional oil and gas development (UD) across the US continues to be at the center of debates regarding safety to health and the environment. This descriptive study evaluated the water quality of private water wells in the Eagle Ford Shale as well as community members’ perceptions of their water. Community members (n = 75) were surveyed about their health status and perceptions of drinking water quality. Water samples from respondent volunteers (n = 19) were collected from private wells and tested for a variety of water quality parameters. Of the private wells sampled, eight had exceedances of maximum contaminant limits (MCLs) for drinking water standards. Geospatial descriptive analysis illustrates the distributions of the well exceedance as well as the well owners’ overall health status. Point-biserial correlational analysis of the haversine distance between respondents and well exceedances revealed four statistically significant relationships {Well 11, Well 12, Well 13, Well 14} with correlations of {0.47, 53, 0.50, 0.48} and p-values of {0.04, 0.02, 0.03, 0.04}, respectively. These correlations suggest that as distance from these northwestern wells increase, there is a higher likelihood of exceedances. Those relying on municipal water or purchased water assessed that it was less safe to drink than those relying on private wells for drinking (p < 0.001, Odds Ratio, OR = 44.32, 95% CI = {5.8, 2003.5}) and cooking (p < 0.003, OR = 13.20, 95% CI = {1.8, 589.9}. Tests of proportional differences between self-reported conditions and provider-reported conditions revealed statistical significance in most cases, perhaps indicating that residents believed they have illnesses for which they are not yet diagnosed (including cancer). In many cases, there are statistically significant differences between self-reported, provider undiagnosed conditions and self-reported, provider diagnosed conditions. Full article