Search Results (9)

Zwitterionic surfactants are a promising option for application in harsh reservoir conditions due to their exceptional stability, compatibility, and interfacial activity. However, surfactant adsorption remains a significant concern. This study investigates the adsorption behavior of zwitterionic surfactants was studied on complex Middle Bakken minerals under high-salinity (total dissolved solids (TDS) = 29 wt%) and high-temperature (90 °C) conditions using the spectrophotometric method. The adsorbents were prepared by grinding Bakken core plugs using a ball mill and sifting them through 40 μm mesh sieves to ensure uniform particle size distribution. The results showed that the Langmuir adsorption model accurately describes the adsorption isotherms of zwitterionic surfactants. The impact of salinity on the zwitterionic surfactants adsorption varied depending on the presence of acidic and/or basic groups in the surfactants. Using Bakken formation brine instead of brine solutions with 2% TDS resulted in a decrease in adsorption of approximately 1.06 ± 0.02 mg/g for CG3 and 0.3 ± 0.04 mg/g for both CD2 and ME1. This reduction was observed in betaine-type zwitterionic surfactants with −COO− functional groups that may gain protons, compared to their adsorption capacities in the 2% TDS brine (2.35 mg/g, 2.1 mg/g, and 1.89 mg/g, respectively). This study provides critical insights into the behavior of interfacial tension (IFT) between crude oil and surfactant solutions, which is vital for optimizing enhanced oil recovery (EOR) processes. The findings underline the importance of surfactant concentration and adsorption characteristics, offering valuable guidelines for practical applications in petroleum reservoir management. Overall, zwitterionic surfactants exhibit higher adsorption on Bakken minerals regardless of the salinity condition. Full article

Geological hydrogen storage, seen as a viable solution for addressing energy demands and mitigating the intermittency of wind power, is gaining recognition. At present, there are no specific studies that estimate hydrogen storage capacity and the potential for wind integration in North Dakota despite the state’s enormous energy resources and capabilities. The study’s key innovation lies in repurposing a region historically associated with oil and gas for sustainable energy storage, thereby addressing the intermittency of wind sources. Moreover, the innovative aspect of this study involves field selection, site screening, characterization, and mathematical modeling to simulate a wind–hydrogen production and geological storage system. A 15 MW wind farm, using real-world data from General Electric wind turbines, is employed to assess storage capacities within the Middle Bakken formation. The study reveals substantial storage potentials in wells W24814, W19693, and W26990, with capacities of 54,000, 33,000, and 22,000 tons, respectively. These capacities translate to energy storage capabilities of 1080, 660, and 440 GWh, with minimum storage durations of 140, 80, and 57 days, respectively, under a 60% system efficiency. By pioneering the integration of wind energy with geological hydrogen storage in a region traditionally dominated by fossil fuel extraction, this research could play a crucial role in advancing North Dakota’s energy transition, providing a blueprint for similar initiatives globally. Full article

The net-effective stress is a fundamental physical property that undergoes dynamic changes in response to variations in pore pressure during production and injection activities. Petrophysical properties, including porosity, permeability, and wave velocities, play a critical role and exhibit strong dependence on the mechanical stress state of the formation. The Williston basin’s Bakken Formation represents a significant reservoir of hydrocarbons within the United States. To investigate this formation, we extracted core plugs from three distinct Bakken members, namely Upper Bakken, Middle Bakken, and Lower Bakken. Subsequently, we conducted a series of measurements of ultrasonic compressional and shear wave velocities, as well as pulse decay permeabilities using nitrogen, under various confining pressures employing the Autolab-1500 apparatus. Our experimental observations revealed that the ultrasonic wave velocities and permeability display a significant sensitivity to stress changes. We investigated existing empirical relationships on velocity-effective stress, compressional-shear wave velocities, and permeability-effective stress, and proposed the best models and associated fitting parameters applicable to the current datasets. In conjunction with the acquired datasets, these models have considerable potential for use in time-lapse seismic monitoring and the study of production decline behavior. The best fitting models can be used to forecast the petrophysical and geomechanical property changes as the reservoir pore pressure is depleted due to the production, which is critical to the production forecast for unconventional reservoirs. Full article

Tight reservoirs around the world contain a significant volume of hydrocarbons; however, the heterogeneity of these reservoirs limits the recovery of the original oil in place to less than 20%. Accurate characterization is therefore needed to understand variations in reservoir properties and their effects on production. Water saturation (Sw) has always been challenging to estimate in ultra-tight reservoirs such as the Bakken Formation due to the inaccuracy of resistivity-based methods. While machine learning (ML) has proven to be a powerful tool for predicting rock properties in many tight formations, few studies have been conducted in reservoirs of similar complexity to the Bakken Formation, which is an ultra-tight, multimineral, low-resistivity reservoir. This study presents a workflow for Sw prediction using well logs, core data, and ML algorithms. Logs and core data were gathered from 29 wells drilled in the Bakken Formation. Due to the inaccuracy and lack of robustness of the tried and tested regression models (e.g., linear regression, random forest regression) in predicting Sw as a continuous variable, the problem was reformulated as a classification task. Instead of exact values, the Sw predictions were made in intervals of 10% increments representing 10 classes from 0% to 100%. Gradient boosting and random forest classifiers scored the best classification accuracy, and these two models were used to construct a voting classifier that achieved the best accuracy of 85.53%. The ML model achieved much better accuracy than conventional resistivity-based methods. By conducting this study, we aim to develop a new workflow to improve the prediction of Sw in reservoirs where conventional methods have poor performance. Full article

Despite the implementation of hydraulic fracturing technologies, the oil recovery in tight oil reservoirs is still poor. In this study, cationic, anionic, and nonionic surfactants of various sorts were investigated to improve oil recovery in tight carbonate cores from the Middle Bakken Formation in the Williston Basin. Petrophysical investigations were performed on the samples prior to the imbibition and core-flooding experiments. The composition of the minerals was examined using the XRD technique. To investigate the pore-size distribution and microstructures, nitrogen adsorption and SEM techniques were applied. The next step involved brine and surfactant imbibition for six Bakken cores and two Berea sandstone cores. The core samples were completely saturated with Bakken crude oil prior to the experiments. The core plugs were then submerged into the brine and surfactant solutions. The volume of recovered oil was measured using imbibition cells as part of experiments involving brine and surfactant ingestion into oil-filled cores. According to the findings, oil recovery from brine imbibition ranges from 4.3% to 15%, whereas oil recovery from surfactant imbibition can range from 9% to 28%. According to the findings, core samples with more clay and larger pore diameters produce higher levels of oil recovery. Additionally, two tight Bakken core samples were used in core-flooding tests. Brine and a separate surfactant solution were the injected fluids. The primary oil recovery from brine flooding on core samples is between 23% and 25%, according to the results. The maximum oil recovery by second-stage surfactant flooding is approximately 33% and 35%. The anionic surfactants appear to yield a better oil recovery in tight Bakken rocks, possibly due to their higher carbonate mineral concentrations, especially clays, according to both the core-scale imbibition and flooding experiments. For studied samples with larger pore sizes, the oil recovery is higher. The knowledge of the impacts of mineral composition, pore size, and surfactant types on oil recovery in tight carbonate rocks is improved by this study. Full article

A recent study by the Wall Street Journal reveals that the hydrofractured horizontal wells in shales have been producing less than the industrial forecasts with the empirical hyperbolic decline curve analysis (DCA). As an alternative to DCA, we introduce a simple, fast and accurate method of estimating ultimate recovery in oil shales. We adopt a physics-based scaling approach to analyze oil rates and ultimate recovery from 14,888 active horizontal oil wells in the Bakken shale. To predict the Estimated Ultimate Recovery (EUR), we collapse production records from individual horizontal shale oil wells onto two segments of a master curve: (1) We find that cumulative oil production from 4845 wells is still growing linearly with the square root of time; and (2) 6401 wells are already in exponential decline after approximately seven years on production. In addition, 2363 wells have discontinuous production records, because of refracturing or changes in downhole flowing pressure, and are matched with a linear combination of scaling curves superposed in time. The remaining 1279 new wells with less than 12 months on production have too few production records to allow for robust matches. These wells are scaled with the slopes of other comparable wells in the square-root-of-time flow regime. In the end, we predict that total ultimate recovery from all existing horizontal wells in Bakken will be some 4.5 billion barrels of oil. We also find that wells completed in the Middle Bakken formation, in general, produce more oil than those completed in the Upper Three Forks formation. The newly completed longer wells with larger hydrofractures have higher initial production rates, but they decline faster and have EURs similar to the cheaper old wells. There is little correlation among EUR, lateral length, and the number and size of hydrofractures. Therefore, technology may not help much in boosting production of new wells completed in the poor immature areas along the edges of the Williston Basin. Operators and policymakers may use our findings to optimize the possible futures of the Bakken shale and other plays. More importantly, the petroleum industry may adopt our physics-based method as an alternative to the overly optimistic hyperbolic DCA that yields an ‘illusory picture’ of shale oil resources. Full article

The Bakken Formation is a typical tight oil reservoir and oil production formation in the world. Pore structure is one of the key factors that determine the accumulation and production of the hydrocarbon. In order to study the pore structures and main controlling factors of the Bakken Formation, 12 samples were selected from the Bakken Formation and conducted on a set of experiments including X-ray diffraction mineral analysis (XRD), total organic carbon (TOC), vitrinite reflectance (R_o), and low-temperature nitrogen adsorption experiments. Results showed that the average TOC and R_o of Upper and Lower Bakken shale is 10.72 wt% and 0.86%, respectively. The Bakken Formation develops micropores, mesopores, and macropores. However, the Upper and Lower Bakken shale are dominated by micropores, while the Middle Bakken tight reservoir is dominated by mesopores. The total pore volume and specific surface area of the Middle Bakken are significantly higher than those of the Upper and Lower Bakken, indicating that Middle Bakken is more conducive to the storage of oil and gas. Through analysis, the main controlling factors for the pore structure of the Upper and Lower Bakken shale are TOC and maturity, while those for Middle Bakken are clay and quartz contents. Full article

Artificially intelligent and predictive modelling of geomechanical properties is performed by creating supervised machine learning data models utilizing artificial neural networks (ANN) and will predict geomechanical properties from basic and commonly used conventional well logs such as gamma ray, and bulk density. The predictive models were created by following the approach on a large volume of data acquired from 112 wells containing the Bakken Formation in North Dakota. The studied wells cover a large surface area of the formation containing the five main producing counties in North Dakota: Burke, Mountrail, McKenzie, Dunn, and Williams. Thus, with a large surface area being analyzed in this research, there is confidence with a high degree of certainty that an extensive representation of the Bakken Formation is modelled, by training neural networks to work on varying properties from the different counties containing the Bakken Formation in North Dakota. Shear wave velocity of 112 wells is also analyzed by regression methods and neural networks, and a new correlation is proposed for the Bakken Formation. The final goal of the research is to achieve supervised artificial neural network models that predict geomechanical properties of future wells with an accuracy of at least 90% for the Upper and Middle Bakken Formation. Thus, obtaining these logs by generating it from statistical and artificially intelligent methods shows a potential for significant improvements in performance, efficiency, and profitability for oil and gas operators. Full article

A method was developed to estimate the consumption of CH₄ and the release of CO₂ by gas flaring using VIIRS nighttime data. The results agreed with the field data collected at six stations in Bakken field, North Dakota, USA, within ±50%, as measured by mean relative errors and with a correlation coefficient of 0.75. This improved over the NOAA NightFire estimates, likely due to: (1) more stringent data selection using only the middle portion of cloud-free VIIRS nighttime imagery; (2) the use of a lower heating rate, which is more suitable for the field condition; and (3) more accurate efficiency factors in calculating completeness in combustion and conversion of total reaction energy into radiant energy that can be sensed by a satellite sensor. While using atmospherically-corrected data can further improve the estimate of CH₄ consumption by ~10%, the major uncertainty remains as being the form factor of the flares, particularly the ratio of total surface area of a flare to the cross-section area that was seen by a satellite sensor. Full article