bluuebunny/crossref_metadata_2025 huggingface dataset:
Faktor Kesuksesan Pengusaha UMKM Wanita Muslim Pengguna Kanal Digital
Authors: Fauziah Fenty , Latief Azhar
Published: May 2023

The surefire way to achieve prosperity is entrepreneurship. In the digital era, there are almost no obstacles to starting a business. The only capital is creativity and courage. Anyone can open an online store, without having to open a physical store first, including women. Women business actors are identical to Micro, Small, and Medium Enterprises (MSMEs). Indonesia and Malaysia are countries that have a majority Muslim population. For a Muslim woman, success can be seen when she manages to build a sakinah family. Women's digital entrepreneurship offers flexibility between work and household matters. This study aims to analyze the important factors that help explain the success of Muslim women MSME entrepreneurs who use digital channels in marketing their products. The study was applied through a descriptive-qualitative approach, where the data were primary-based. The objectivity was applied to 103 informants obtained from several MSME communities randomly from Indonesia and Malaysia. We find that social capital is a relevant factor for entrepreneurial success among Muslim women MSME entrepreneurs, the form of social capital is the number of children. This finding supports the idea that Muslim women entrepreneurs who have fewer children tend to spend more time on their business than Muslim women entrepreneurs who have more children. Financial capital projected by income growth also affects success, although income growth is on a small scale. Self-efficacy due to internal factors originating from within MSME female entrepreneurs such as self-confidence and tenacity, they are successful in their business. Religiosity has a significant effect on the success of a Muslim woman entrepreneur.
Insights Into Bitumen Viscosity Reduction Using Ultrasound-Assisted EOR
Authors: Nguele Ronald , Saheed Alade Olalekan , Okawa Hirokazu , Sasaki Kyuro
Published: May 2023

The present work clarifies the mechanisms associated with bitumen viscosity reduction during ultrasound sonication. A Canadian (CDN) and Nigerian (NGR) bitumen, selected for this study, have a respective viscosity of 2,617 and 12,043 cP at room temperature. Two series of ultrasound sonication experiments were performed using an ultrasonic generator and the submersible traducer. A series of experiments at 28, 38 and 200 kHz under ambient (air)-environment revealed that sonicating the oil continuously for 3 h at 200 kHz reduced NGR viscosity from 12,043 to 2,079 cP and the asphaltene content from 3.21 to 1.14 wt.%. Under the same conditions, CDN viscosity reduced from 2,617 to 486 cP and its asphaltene content increased from 5.72 to 8.11 wt.%. A reverse trend was observed at 38 kHz. For an average of 70% viscosity reduction, asphaltene content increases to 7.94 wt.% for NGR and decreases to 1.03 wt.% for CDN. On the other hand, bitumen sonication at 38 kHz under nitrogen (N2), and carbon dioxide (CO2) environment showed that irradiating NGR for 3 h under an N2 environment resulted in the lowest oil viscosity of 3,274 cP. However, the asphaltene content increases to 16.3 wt.%. Changing the gas environment to CO2 and air could reduce the viscosity to 4,415 and 9,773 cP, respectively. The asphaltene content decreases to 15.1 and 2.37 wt.%, concurrently. No direct relation between asphaltene content and viscosity reduction was established. Nevertheless, the viscosity reduction is influenced either by the applied frequency or gas environment. The minimum energy required to initiate the flow increased with the applied frequency and was fairly altered by the change in the gas environment.
Kuparuk Field Reservoir Management After 40 Years
Authors: Jensen Trond B , Lewis Adam M , Little Laird D , Neely Thomas G , Scheihing Mark H , Stevenson Mark D , Van Nostrand Dominique , Versteeg Joe R
Published: May 2023

The giant Kuparuk Field (Figure 1), the second largest oil field on the Alaska North Slope and one of the largest oil fields in the United States, has been on production for 41 years. The field, a legacy asset in the ConocoPhillips portfolio, contains more than 7.5 Bstb OOIP with 2.5 Bstb in the C Sands and 5.0 Bstb in the A Sands. Production commenced in December 1981 and has cumulated to date more than 2.5 Bstb oil through water-flooding, immiscible water-alternating gas (IWAG) and miscible water-alternating-gas (MWAG) injection. Currently, the field produces about 60,000 stb/d oil, 515,000 bbl/d water and 105 MMscf/d gas, and injects 625,000 bbl/d water and 80 MMscf/d gas through 3 central processing facilities (CPF1, CPF2, and CPF3, located as shown in Figure 1), 45 drillsites, and about 700 active wells.

Although the Kuparuk Field is mature, recent studies highlight the potential to optimize the oil recovery. Static and dynamic data along with benchmark studies indicate that the underlying Kuparuk A Sands are of lower maturity than the overlying Kuparuk C Sands. Significant A Sands recovery improvement is possible with strategic reservoir management practices. Several activities were undertaken to understand relative immaturities across the field and investigate methods to improve the performance of Kuparuk A Sands. These include: identifying geologically controlled reservoir performance regions, developing a state-of-the-art full field reservoir model, testing pattern realignment that combines infill drilling with reconfiguration of existing wellbores, and conducting injectivity treatments in various parts of the field. The analysis of available data shows the benefits of increasing the throughput in the Kuparuk A Sands through voidage balancing, improved produced water and gas handling strategies, waterflood pattern realignment, continued in-fill drilling, and increased injectivity. Kuparuk reservoir management has been revised to focus future activities around these core strategies tailored to specific reservoir regions. The intent of this paper is to document strategies that can be implemented to revitalize mature waterflood fields, specifically those that have been developed with commingled reservoirs.
Neural Network-Assisted Clustering for Improved Production Predictions in Unconventional Reservoirs
Authors: Cornelio Jodel , Mohd Razak Syamil , Cho Young , Liu Hui-Hai , Vaidya Ravimadhav , Jafarpour Behnam
Published: May 2023

Given sufficiently extensive data, deep-learning models can effectively predict the behavior of unconventional reservoirs. However, current approaches in building the models do not directly reveal the causal effects of flow behavior, underlying physics, or well-specific correlations; especially when the models are trained using data from multiple wells of a large field. Field observations have indicated that a single reservoir does not have similar production behaviors. This makes pre-filtering the data to build local models that capture region specific correlations more pertinent than a single global model that will provide averaged-out predictions from different correlations.

In this work, we investigate a sophisticated network architecture to expedite the clustering process by training the global model. We utilize attention-based (transformer) neural networks for the input data before mapping to the target variable to extract the attention scores between well properties and the production performance. We leverage the interpretability from these attention-based models to improve the prediction performance for data-centric models derived from clustered datasets. We show the benefits of building local models that are more accurate as they learn correlations that are more region/data specific. Specifically, by utilizing the attention mechanism, we can separate and curate data subsets to train local models, improving the prediction performance by reducing the variability in the entire field.
An Uncertainty Risk Evaluation Tool for Wellbore Leakage Prediction for Plug and Abandonement (P&A)
Authors: Ugarte Esteban R. , Salehi Saeed
Published: May 2023

Oil and gas wells leakage is a major concern due to the associated risks. Potential issues include habitat fragmentation, soil erosion, groundwater contamination, and greenhouse gas emissions released into the atmosphere. An estimated 2 million abandoned oil and gas wells are believed to be leakage. Proper Plug and Abandonment (P&A) operations are required to ensure these wells are correctly disposed of from their useful operational life. This study aims to build an uncertainty evaluation tool to statistically classify the risk of a well from leaking based on their well information (age, location, depth, completion interval, casings, and cement). Data consists of leakage reports and available well data reports from Alberta Energy Regulator (AER) in Canada. Multiple preprocessing techniques, including balancing the data, encoding, and standardization, were implemented before training. Multiple models that included Naïve Bayes (NB), Support Vector Machine (SVM), Decision Trees (DT), Random Forest (RF), and K-Nearest Neighbors (KNN) were compared to select the best-performing for optimization. RF outperformed the other models and was tuned using hyperparameter optimization and cross-validation. The final model's average accuracy was 77.1% across all folds. Multiple evaluation metrics, including Accuracy, Confusion Matrix, Precision, Recall, and Area Under the ROC Curve (AUC), were used to assess the model and each class against the rest. Feature importance showed an even distribution across the different features used. The model presented in the study aimed to classify wells and label the leakage risk based on the well information associated with its components. This risk evaluation tool could help reduce gas emissions by 28.2% based on the results obtained. This tool can classify the wells to speed the selection process and prioritize wells with higher leakage risk to perform P&A operations and minimize emissions.
From Nano-Pores to Wellbores and Back: Scale-Dependent Fluid Flow and Storage Systems in Unconventional Reservoirs
Authors: Reichhardt David , Hoffman B. Todd
Published: May 2023

Pore-scale dependent phase behavior describes a decrease in the hydrocarbon phase envelope as pore throat size decreases. This phenomenon is well documented in terms of confining effects on phase behavior with several analytical fluid models proposed that account for these effects. Results from a limited number of numerical reservoir models show the effects pore-scale phase behavior has on total production. However, fewer studies consider fluid transfer between different scale pore networks as a function of scale-dependent phase behavior. This work investigates fluid transfer between different scale pore networks related to scale-dependent phase behavior and the affects it has on production and fluid composition in the pore networks.

A commercially available reservoir simulator is used with a dual porosity/permeability grid and scale-dependent fluid models to study the fluid transfer between pore networks. Fluid tracking is used to trace fluid phases and components that originate in both the nanoscale and macroscale pore networks. Fluid transfer between pore networks is considered at both the pore network scale and at the well stream scale by tracking the fluid components from nano-scale pores into macro-scale pores and ultimately to the well bore. The results from the model are used to quantify fluid transfer between pore networks.

The results of the study show how the confining effects on fluid phase behavior affect fluid production rates and gas-oil ratios by linking the pore scale processes to the well stream scale production. For example, as fluid moves from the nanoscale pores, where the bubble point is suppressed and the fluid retains the initial solution gas-oil ratio (Rs), into the macro scale pores, the fluid in the macroscale pores is enriched by the nanoscale pore fluid.

This work provides three main contributions to an improved understanding and characterization of unconventional plays. The first is demonstrating the ability to simulate the confining effects on fluid phase behavior using commercially available reservoir simulators. Second is the ability to capture some of the unique production trends observed for tight oil reservoirs, e.g., extended periods of stable GOR, when modeling these reservoirs. The third contribution is in tight oil EOR, providing insight into the composition of the fluid that remains in the pore networks following primary depletion or at the onset of an EOR process.
Evaluation of CO2 Storage Potential During CO2 Mobility Control Optimization for Enhanced Oil Recovery
Authors: Hanamertani Alvinda Sri , Yu Ying , Elkhatib Omar , Ahmed Shehzad , Jiao Zunsheng , McLaughlin Jonathan Fred
Published: May 2023

CO2 mobility control by foam technology has enabled better sweep efficiency and, consequently, oil productivity during enhanced oil recovery (EOR) processes. Simultaneously with enhancing oil production, there is a sound potential for the in-situ generated foam to enhance CO2 storage potential. However, the impact of the different in-situ foam generation strategies on the combined goal of maximum oil production and carbon storage is not well elucidated in the literature. In this study, we methodically evaluate the simultaneous optimization of CO2 storage and oil recovery utilizing multiple injection strategies. Three flow experiments were performed in Indiana Limestone core samples deploying a zwitterionic surfactant as the foaming agent. In the first experiment, we investigated the use of pure supercritical CO2 (scCO2) on the oil production and the extent of CO2 trapping in the used core, served as the base case. In the second and third experiment, we pre-flushed the porous media with a 0.5 wt% and 1 wt% surfactant solution slugs, respectively, followed by scCO2 injection to evaluate the impact of a single-cycle surfactant alternating gas (SAG) injection strategy. Then, co-injection of the foaming agent and scCO2 was attempted in both scenarios. The results show that the surfactant/scCO2 co-injection method effectively controlled the mobility of scCO2 by creating an advantageous environment and providing a continuous supply of surfactant solution for in-situ foam generation. Additionally, increasing surfactant concentration encouraged more effective mobility control due to the formation of higher stability foam and, consequently, improves the sweep efficiency and oil displacement process. In term of CO2 storage, performing a single-cyle SAG led to an increase in the volume of CO2 stored by 51% and 66% in the second and third experiments, respectively, relative to the base case. Based on the calculated volume element exchange parameter, it was noticed that the CO2 storage effect during CO2 flooding at 0.5 wt% and 1 wt% surfactant concentrations was relatively similar. On the other hand, by implementing the co-injection method, the higher surfactant concentration (1 wt%) results in better oil recovery but lower CO2 storage potential compared to 0.5 wt%. The storage effect using 0.5 wt% surfactant solution was almost two times higher than the storage effect at 1 wt% concentration. We found that the higher foam strength due to increased surfactant concentration dominantly leads to more residual oil displacement than inducing more CO2 storage. This finding ascertains that a thorough investigation of the injection strategy and composition is crucial before associating the CO2 storage with CO2 EOR or CO2-foam EOR processes to achieve the most desirable ratio between stored CO2 and oil recovery. Overall, the in-situ foam generation has proven to be beneficial to the dual purposes of carbon geo-storage and EOR.
Optimizing Oil Recovery and CO2 Sequestration in Carbonate Reservoirs using Voidage Replacement and Production Balancing Methods
Authors: Hamdi Zakaria , Al-hadrani Mohammed Ahmed , Bataee Mahmood
Published: May 2023

Replacement of voidage relates to the method of injecting liquids to replace oil, water and gas inside the reservoir. The technique for voidage replacement is the volume of injected fluids in the barrel over the volume they got produced. Injected liquids may be wasted outside the floodable quantity of the pore in the reservoir during injection, because of many factors such as bad cement in the casing leakage, etc. A Voidage Replacement Ratio of 1.2 is chosen to preserve the replaced fluid pressure of the reservoir. The balancing Production technique relates to the determination of a scheduled rate of production to be accomplished at a particular time. To preserve the reservoir pressure, a production balancing ratio of 1.2 should be selected for a higher production rate that is balanced with the injected fluids. The balancing production approach involves ensuring that the liquids injected fulfil the production ability needed to prevent any reservoir pressure unbalance. The water alternating gas (WAG) method is the technique to improve oil recovery by injecting water to enhance sweep effectiveness. If gas is being injected into this technique, the viscosity of the oil will be reduced, making it convenient for the water to sweep it well into the production wells. WAG-365 case of a 365-day cycling period is the best one to be selected as longer time provides the gas with the opportunity to guarantee two things, sweeping the residual oil that is immobile and trapped inside the tight pores and also dissolving in the oil and reducing its viscosity. CO2 sequestration relates to the subterranean CO2 injection method to prevent the atmosphere from CO2 emissions from burning fossil fuels that subsequently lead to global warming and hazardous climate change. Throughout the WAG method, CO2 is used and injected to be stored as a solution and the quantity of CO2 stored is defined by changing the solubility of the gas. The more the gas's solubility results in a large quantity of stored CO2.
Application of Two Novel Enhanced Oil Recovery Processes in the Bakken Shale
Authors: Downey Robert , Venepalli Kiran
Published: May 2023

Oil production via horizontal wells with multistage fracture stimulation treatment completions in the Bakken shale of North Dakota and Montana began in 2003. Since then, over 19,000 Bakken shale horizontal wells have been completed and placed into production. Oil production from horizontal Bakken shale oil wells peaked in November 2019 at 1.5 million barrels/day, and is at about 1.2 million barrels/day as of September, 2022 (EIA). There have been several shale oil EOR tests conducted over the last several years, involving the injection of water, CO2 and natural gas.

This paper builds upon shale EOR modeling work described in a 2019 NETL report. In that report, a compositional simulation model of the Bakken was constructed, and a production history match on primary oil, gas and water production from a group of wells was obtained. The match model was then used to evaluate the enhanced oil recovery via cyclic injection of CO2, dry gas, and wet gas. This paper utilizes some data from that report to assess two novel, proprietary shale oil EOR processes in the Bakken, in the same area of the Williston Basin. The paper illustrates how these proprietary shale oil EOR processes may be implemented at lower BHP to mitigate interwell communication, while enabling greater oil recovery than via injection of water, CO2 or natural gas.

Compositional reservoir simulation modeling of the two novel EOR processes in the modeled Bakken shale wells indicates potential incremental oil recoveries of 200% and 300% of primary EUR may be achieved.

The two novel shale oil EOR methods utilize a triplex pump to inject a liquid solvent having a specific composition into the shale oil reservoir, and a method to recover the injectant at the surface, for storage and reinjection. One of the processes enables further enhanced oil recovery via cyclic fracture stimulation at the start of the EOR process. The processes are fully integrated with compositional reservoir simulation to optimize the recovery of residual oil during each injection and production cycle.

The patent pending shale oil EOR processes have numerous advantages over cyclic gas injection - shorter injection time, longer production time, smaller, lower cost injection volumes, no gas containment issue - much lower risk of interwell communication, elimination of the need to buy and sell injectant during each cycle, much better economics, scalability, faster implementation, optimization via integration with compositional reservoir simulation modeling, and lower emissions. If implemented early in the well life, their application may preclude the need for artificial lift, to produce more oil sooner, resulting in a shallower decline rate and higher reserves.
Hydrogen Generation from Heavy Oils via In-situ Combustion Gasification
Authors: Song Ping , Li Yunan , Yin Zhen , Yuan Qingwang
Published: May 2023

In-situ combustion (ISC) is a technology used for enhanced oil recovery for heavy oil reservoirs. In two ISC field pilots conducted in 1970s to 1980s in Canada, 10-20% mole fraction of hydrogen (H2) was produced accidentally. This presents a potential opportunity for petroleum industry to contribute to the energy transition by producing hydrogen directly from petroleum reservoirs. However, most ISC experiments have reported no or negligible hydrogen production, and the reason remains unclear. To address this issue, this study focuses on hydrogen generation from bitumen through in-situ combustion gasification (ISCG) at a laboratory scale. CMG was used to simulate the ISCG process in a combustion tube. Kinetics from previous ISC experiments and reactions for hydrogen generation were incorporated in the models. Heavy oil, oxygen, and water were simultaneously injected into the tube at a certain temperature. The ranges of key parameters were varied and analyzed for their impact on hydrogen generation. The study found that maintaining a temperature above 400 °C is essential for hydrogen generation, with higher temperatures yielding higher hydrogen mole fractions. A maximum of 28% hydrogen mole fraction was obtained at a water-oxygen ratio of 0.0018:0.9882 (volume ratio at ambient conditions) and a temperature about 735 °C. Higher oxygen content was found to be favorable for hydrogen generation by achieving a higher temperature, while increasing nitrogen from 0 to 78% led to a decrease in hydrogen mole fraction from 28% to 0.07%. Hydrogen generation is dominated by coke gasification and water-gas shift reactions at low and high temperatures, respectively. This research provides valuable insights into the key parameters affecting hydrogen generation from bitumen at a lab scale. The potential for petroleum industry to contribute to energy transition through large-scale, low-cost hydrogen production from reservoirs is significant.
Wellbore Leakage and Seismic Risk Assessments for Geological Carbon Dioxide Storage in Saline Formations in Kern County, California
Authors: Kim Tae Wook , Kohli Arjun , Li Yunan , Kovseck Anthony Robert
Published: May 2023

We evaluate the potential for CO2 leakage along pre-existing wells and through the formation caprock as well as the probability of inducing slip on faults during CO2 injection and storage in a saline formation in the Southern San Joaquin Basin. Our model considers 0.6 Mt CO2/y injection for 47 years and monitoring for an additional 100 years.

The prospective CO2 storage site was selected based on previous geospatial and economic analysis of emitters and storage sites in Kern County (Kim et al., 2022). Reservoir simulation was used to calculate the pressure and CO2 saturation. Then, risk assessment tools were used to estimate potential leakage rates through the overlying formations and along vertical wells. The stress state of the storage formation was determined based on regional stress information, earthquake moment tensor inversion, and well log data. Fault slip potential software was used to calculate the probability of inducing slip on faults considering a distribution of geomechanical parameters and fault orientations. We also study the historical seismicity of the area and identify seismological metrics that may help to distinguish natural from induced events.

There was no predicted leakage for CO2 and brine into the USDW with an assumption of wellbore permeability less than 10 mD (a value greater than that of a typical wellbore cement). The worst case for leakage assessment, with less than 1 % probability, assumed that the effective permeability of the existing wellbore is extremely high (30–50 mD). Nevertheless, the ratio of leaked CO2 mass to injected mass is less than 3.8 x10−6 (0.00038%). No impacts on a drinking water aquifer are predicted. The effective wellbore permeability is the most sensitive parameter to assess the leakage rate. The probabilistic fault model indicates that the pressure buildup should be limited to 500 psi (3.45 MPa) within 1 km of the injection site in order to minimize the risk of inducing slip on large faults.

This study provides a standard procedure to evaluate the potential for CO2 leakage and induced fault slip for any candidate CO2 storage site using publicly available data. This type of probabilistic risk assessment is critical in order to encompass the uncertainties in hydrological and geomechanical parameters and any variability in operating conditions.
Improving Economics for Abandoning Orphaned and Idle Oil and Gas Wells by Providing Storage for Pulverized Blades from Wind Turbines
Authors: Ikeocha Elena , Ershaghi Iraj
Published: May 2023

In a rush to install more renewable energy resources, we must carefully consider and mitigate the legacy issues with end of life waster from new solar and wind turbine installations. This paper is about a potential solution for handling legacy assets from wind turbine blades. The paper presents the economic viability to consider well internal capacities as storage sites as well as analyzes the environmental hazards of landfilling the blades. Bisphenol A (BPA) is a chemical used in wind turbine blades. Storage in landfills can put the future health of natural resources and the surrounding areas at risk. BPA can leak out of the dust particles and be hazardous to people and the environment. BPA also degrades in water and sediments under microbial processes. The increased risk of BPA leaching into groundwater resources and the soil from wind turbine blade landfills can damage the food chain and can harm future generations due to exposure to the contaminated resources. The solution discussed here is a potential use of the casing storage of idle wells for housing pulverized blades mixed with Portland cement when the wells are considered for plug and abandonment.
California Outer Continental Shelf Platform Decommissioning Update, Outlook, and Challenges
Authors: Smith John Bridge , Byrd Robert Clark
Published: May 2023

The authors have been working with the challenges related to decommissioning facilities offshore California since 1996. In a 2018 OTC paper (OTC-28844-MS) they reviewed the challenges for offshore facility decommissioning in this region. This paper reviews and updates the oil and gas platform decommissioning projects being conducted on the federal Outer Continental Shelf (OCS) offshore California and the decommissioning outlook for OCS platforms through the end of this decade. There are a total of 23 oil and gas platforms on the federal OCS offshore California which are submerged lands located more than three nautical miles from the coastline. The authors project that one-third of the 23 OCS platforms and one state water platform are likely to be decommissioned by the end of the decade, and at least 50 percent of the OCS platforms are likely to be removed by the middle of the next decade. Three of the eight OCS platforms being decommissioned, if fully removed, would each establish world water depth records for removing conventional steel platform jackets from the seafloor. The paper also describes the major technical, logistical, environmental, and regulatory challenges operators face in planning and conducting decommissioning projects offshore California.
Natural Extracted Waste Materials for Breaking Crude Oil Emulsion
Authors: Adewunmi Ahmad A. , Kamal Muhammad Shahzad , Gbadamosi Afeez , Patil Shirish
Published: May 2023

This study was performed to examine the efficacy of corn husks (CH) fine particles as potential natural demulsifier for breaking crude oil emulsion. Stable emulsions were formed using distilled water/crude oil and oil-water ratio was 4:6. The concentrations of CH particles ranging from 0.25, 0.5, 0.75, and 1% were added into vials containing the prepared emulsions and demulsification test was conducted inside the oven at 75 °C. Rheology was used to illustrate the demulsification mechanism of CH as potential demulsifiers. According to the experimental outcomes, the demulsification activity from the bottle test showed that water removal increased with the increasing CH concentration. The demulsification efficiency (DE) of 0.25, 0.5, 0.75, and 1% CH was 8.33%, 50%, 73.33% and 81.67%, respectively; after 60 minutes of demulsification duration. Rheological characterization showed that the incorporation of CH particles caused the reduction of emulsion viscosity which indicated the breaking of emulsion and separation of oil and water. Optical microscopic analysis revealed the morphologies of emulsion immediately after preparation, as well as oil and water phases after separation.
Beneficial Advantages of Nanoparticle-Enhanced Surfactant-Assisted Low Salinity Waterflooding Process
Authors: Fakir Shasanowar Hussain , Belhaj Ahmed Fatih , Singh Navpreet , Sarma Hemanta Kumar
Published: May 2023

The application of nanoparticles (NPs) to improve oil recovery is gaining wide acceptance in the petroleum industry in recent times. Due to their size and set chemical characteristics, NPs can be used to enhance oil recovery in carbonate reservoirs by altering the rock wettability and reducing oil–brine interfacial tension (IFT). Also, when used with surface-active agents like surfactant (cationic, anionic or non–ionic) in low–salinity waterflooding (LSWF), NPs can enhance the performance of surfactant. This study focuses on the implications of combining green NPs with surfactant and low–salinity water for EOR applications in carbonate reservoirs. A NP was synthesized from a green source, rice husk, and then characterized using XRD, FTIR, TGA and SEM analyses. A cationic surfactant, Aspiro S 6420, was added in the nanoemulsion of silica nanoparticle (SNP) and 1% diluted seawater (dSW). The SNP-Surfactant-1%dSW nanoemulsion was investigated for its beneficial effects for EOR applications. Zeta potential measurements were carried out for various brine dilutions, then for 1% dSW and surfactant, and finally 1%dSW–Surfactant–SNP nanoemulsions. The measurements showed that the zeta potentials are highly positive, confirming the stability of the nanoemulsions and alteration of rock wettability. Interfacial tension (IFT) between oil and brine were measured at a temperature of 86°C. The addition of surfactant (Aspiro S 6420) led to significant drop in IFT between oil and brine. Finally, when SNPs were added to the 1%dSW–Surfactant emulsions, the IFT reduced significantly, confirming that the combination of low salinity brine–cationic surfactant (Aspiro S 6420)–SNP can be used as a promising injection fluid to recover oil from carbonate reservoirs.
Determining the Storage Capacity of a Saltwater Disposal Reservoir in Practice
Authors: Wu Xingru , Childers David R. , Dai Lei , Shaffer Kelly
Published: May 2023

Produced water is commonly co-produced with oil and gas production and requires safe disposal in subsurface reservoirs. Knowing the amount of produced water that can be safely injected into the reservoir is important for disposal operations. While the methods of reservoir hydrocarbon storage are abundant in literature, the granularity of handling water injection capacity is rare, probably due to the misconception that production is similar to injection into a formation. The knowledge of hydrocarbon reservoir petrophysics shines some light on the problem. However, it is far from sufficient to make an economically viable decision as injecting water into the reservoir dramatically differs from producing it.

Many practitioners take for granted that knowing the pore volume of the target formation would be sufficient to determine the storage volume. The actual water injection capacity is the product of the pore volume of the formation, total compressibility of the system, and maximum allowable pressure difference. Since the stress-strain relationship of a porous medium depends on the frequency and magnitude of the loading and unloading process, the total compressibility would be different. The maximum allowable injection pressure and reservoir pressure are functions of in-situ stresses, injection temperature and pressure, and reservoir geomechanical parameters, all of which have significant uncertainty. In practical design, we must consider all parameters and their respective uncertainties. This paper presents a procedure for determining the injection capacity through an in-depth discussion of involved parameters and their associated uncertainties from estimation and measurements. This paper will also demonstrate our practice using a field example as our case study to show our suggested approach.
The Effect of Fracture Surface Roughness on Propped Fracture Conductivity Using 3D-Printed Fracture Surfaces
Authors: Sistrunk Carrie , Brashear Andrew Travis , Hill Dan , Zhu Ding , Tajima Tohoko
Published: May 2023

When rocks are fractured in tension, the fracture surfaces created are rough, with a wide range of surface morphologies possible. In previous studies of propped fracture conductivity using fractured samples, the fracture surface topography was found to have a strong influence on fracture conductivity and stimulation efficiency. Fracture surface patterns (relatively uniform, randomly rough, step changes, ridges and valleys) strongly affect propped fracture conductivity. Different types of surfaces can result in propped fracture conductivities differing by an order of magnitude or more for identical proppant loading conditions. To generate quantitative correlations including surface topographic effects, consistent samples with well-defined surfaces should be used in the experiments. However, when using actual rock samples to create realistic fracture surfaces by fracturing them in tension, the surfaces created are never the same, even using small samples all taken from the same block. This lack of repeatability in fracture surfaces greatly complicates identification of the effects of the rough surfaces on propped fracture conductivity.

To overcome this, we created repeatable rough fracture surfaces using 3D-printing technology. First, we geostatistically generated a numerical depiction of a rough fracture surface. Then the surface was printed with resin using a 3D-printer. The hardened resin model of the rock sample was used to make a mold, which was in turn used to create a rock sample made of cement. High strength cement was used so that the samples had similar mechanical properties to unconventional reservoir rocks. With this methodology, we created multiple samples with identical surface roughness and features, allowing us to isolate and test other parameters, such as proppant size and concentration.

Fracture conductivity tests were conducted using a modified API conductivity cell and artificial rock samples that are nominally 7 inches long and 2 inches wide. A well-established protocol to generate propped fracture conductivity as a function of closure stress was employed to test three different proppant concentrations on identical rough surfaces. For all three experiments, 100 mesh sand was used. The study demonstrates how proppant concentration affects propped fracture conductivity behavior in a systematic way.
Implementation of Renewable Technologies and Its Impact on Oil & Gas Resources Under Energy Market Dynamics Worldwide
Authors: Yurukcu Mesut , Yilmaz Koray , Yondemli Hande , Oskay Mehmet Melih
Published: May 2023

Investment in renewable energy resources and technologies from the oil and gas sector has increased consistently in the past two decades, turning the industry into one of the primary sources of capital for these newer energy sources, despite the potential that renewables possess to replace oil and gas since 1859. Renewables can be considered complementary, or competitors to oil and gas resources. Market forces respond differently to investments in renewables and the dynamics that these transfers of capital trigger in the general environment. For example, in Southern California and Oman, renewables are used to improve and decarbonize various oil and gas production processes. Meanwhile, alternative energy sources have displaced significant market oil and gas shares in other parts of the world, significantly altering supply and demand dynamics. Part strategy, part environmental commitment, the oil and gas sector has invested increasingly more capital in renewables in the past few decades. Despite the seemingly competing nature of its relationship with alternative energy sources, markets have adapted to work under a more collaborative approach, at least in the medium term.

The literature has covered the advent of renewables in detail, but it has focused less on the response from the oil and gas markets after the changes brought about by this arrival. We bridge that gap while exploring the advantages and challenges of maintaining a complementary relationship and how a strong investment in renewables can be the way forward for the oil and gas sector. This paper explores the dynamics between renewable energies and the oil and gas industry, both as complementary sources also as competing resources, that exacerbate or retreat depending on factors like geography, regulations, or market forces.
Field-Scale Multi-Stage and Multi-Objective Optimization of Rate and Concentration for Polymer Flooding
Authors: Zhang Ruxin , Li Ao , Chen Hongquan , Datta-Gupta Akhil , Chitale Ashish , Shekher Sunit , Kumar Ritesh , Das Joyjit
Published: May 2023

Field-scale simultaneous optimization of well rate and polymer concentration is challenging due to the geologic heterogeneity, large number of wells, and operational constraints. This paper proposes a multi-stage optimization strategy to achieve a multi-objective goal: maximize cumulative oil production and minimize cumulative polymer injection.

The proposed optimization strategy follows a sequential step: well rate optimization followed by polymer concentration optimization. In the first stage, streamline-based method is used to adjust the water injection rate and liquid production rate for hundreds of wells. This method equalizes the well pair efficiency that quantifies the amount of oil recovered per barrel of water injection, to maximize oil recovery. Key injectors are selected from the first stage and included in the multi-objective optimization for the second stage. A novel stochastic approach, multi-objective global and local surrogate-assisted method (MO-GLS), is utilized to optimize polymer concentration, to maximize cumulative oil production while minimizing cumulative polymer injection. This method considers a global prescreen and local search to obtain the trade-off solutions along the pareto front based on a dominance relation. Proxy model is built inside and updated during the iteration to improve optimization efficiency and particle swarm optimization is adopted as the optimizer for a fast convergence rate.

After multi-objective optimization, multiple trade-off solutions can be found along the pareto front, which have lower parameter uncertainty compared to the initial population. The optimization results are visualized using streamlines, which provide insights into the improvement in sweep efficiency from rate and concentration optimization. The sequential optimization workflow conducted in this paper provides theoretical basis and operational recommendations for the optimization of well rate and polymer concentration. The practical feasibility of the approach is demonstrated through a large-scale field application.
Machine Learning Assisted Well Placement Optimization
Authors: Davudov Davud , Venkatraman Ashwin , Mabadeje Ademide O. , Malkov Anton , Singh Gurpreet , Dindoruk Birol , Al-Aulaqi Talal
Published: May 2023

Well placement optimization is a complicated problem which is usually solved by direct combination of reservoir simulators with optimization algorithm. However, depending on complexity of the reservoir model studied, thousands of simulations is usually needed for accurate and reliable results. In this research, we present a novel approach – machine learning (ML) assisted proxy model that combines reservoir simulations and reduced physics model to reduce computational cost.

In the proposed model framework, first several (depending on the complexity of the problem) uniformly distributed random coordinates are selected. These chosen coordinates are considered as data points for ML model. For the chosen coordinates (training set) reservoir simulations are executed and NPV/recovery values are calculated (target variable). Spatial locations as well as petrophysical properties of the same coordinates extracted from simulation model are also used as an input to the ML model. ML model is further improved by combining with Fast Marching Model (FMM) which is a robust reduced physics model. The inclusion of FMM helps identify drainage volume for producers and hence enhance model training. Finally, the trained ML model is coupled with stochastic optimization algorithms to determine infill well location with highest NPV/recovery.

Using an example field data, we present two specific cases of using proposed model: a) for greenfield with a single new well, b) for greenfield with multiple new wells. Results indicate that developed ML model can predict NPV with around 96% accuracy (testing score). This gives great confidence in predictions from the trained hybrid model that can be used as a proxy model for reservoir simulations. Coupling the trained hybrid model with Particle Swarm Optimization (PSO), the location of the new producers with maximum NPV are determined. The results are further confirmed with an exhaustive search from all potential locations.

A novel approach is presented to show how traditional physics-based approaches can be combined with machine learning algorithms to optimize well placement. Such approaches can be integrated in current greenfield and brownfield reservoir engineering workflow to drastically reduce decision making times.
Experimental Study: Investigating the Anions and Cations’ Effects on the Elasticity of the Anionic and Cationic High Viscosity Friction Reducers
Authors: Ge Xiaojing , Biheri Ghith , Imqam Abdulmohsin , Bai Baojun , Zhang Yuwei
Published: May 2023

High viscosity friction reducers (HVFRs) are widely used as friction-reducing agents and proppant carriers during hydraulic fracturing. The reuse of produced water has gained popularity due to environmental and economic benefits. Currently, the field’s most commonly used friction reducers are anionic and cationic HVFRs. Anionic HVFRs are typically pumped with freshwater, while cationic HVFRs are used with high Total Dissolved Solids (TDS) produced water. Cationic friction reducers are believed to have better TDS tolerance, friction reduction performance, and proppant transport capabilities compared to anionic friction reducers under high TDS conditions due to their superior viscoelastic properties. In addition, the impact of different anions and cations on the viscosity of HVFRs has been thoroughly studied, and viscosity reduction mechanisms include charge shielding, increasing the degree of hydrolysis, and forming coordination complexes. However, anions and cations’ effects on the elasticity of HVFRs still remain to be investigated. Besides, most previous experimental studies either do not specify experimental procedures or control the experimental variables well. Therefore, the ultimate objective of this experimental study is to analyze various cations and anions’ effects on the elasticity of anionic and cationic HVFRs comparably and precisely with experimental variables well controlled. Two hypotheses based on anions and cations’ effects on the viscosity of HVFRs are proposed and will be tested in this study. First, the elasticity reduction of anionic HVFRs is mainly due to cations, whereas the elasticity reduction of cationic HVFRs is mainly due to anions. Second, the salts’ effects on the elasticity reduction of HVFRs should follow the same trend as the salts’ effects on the viscosity reduction of HVFRs. For anionic HVFRs, monovalent Alkali metals should have a similar effect; divalent Alkaline earth metals should have a similar effect; transition metals should have the most severe effect. For cationic HVFRs, SO42- should have more pronounced effects than Cl-. To demonstrate both hypotheses, an anionic and a cationic HVFR at 4 gallons per thousand gallons (GPT) were selected and analyzed. The elasticity measurements of both anionic and cationic HVFRs were conducted with deionized (DI) water and various salts respectively. Fe3+ and H+ (or pH) effects were specifically investigated. The results showed both hypotheses were accepted.