Enhance Oil Production Research Articles

A Study on Future Population Dynamics of Indigenous Earthworm Species in Golaghat District of Assam, India

This study presents a pioneering exploration into the population dynamics of indigenous earthworm species in the Golaghat district of Assam, India, through the lens of mathematical modeling. Recognizing the integral role of earthworms in enhancing soil productivity and ecosystem health, we embarked on a detailed longitudinal analysis spanning from 2018 to 2023 to assess their population trends across different seasons and subdivisions within the district. Utilizing the principles of Mathematical Biology, we employed the Malthus Growth model and the Logistic Growth model to estimate future population trajectories of earthworm species, integrating biological insights with mathematical rigor. Our methodology, combining extensive field data collection with sophisticated mathematical modeling, provides a replicable framework for similar ecological studies. This study contributes to the growing field of Mathematical Biology, offering a novel approach to understanding the complex interactions within ecosystems and the impact of environmental changes on key species. The outcomes offer valuable insights into sustainable agricultural practices and biodiversity conservation in tropical and subtropical regions, emphasizing the critical role of indigenous earthworm species in maintaining soil health and ecosystem services. Our findings reveal significant seasonal variations and highlight the resilience of these species in the face of ecological changes. The models suggest distinct population growth patterns, with the Logistic model providing a more realistic projection considering environmental constraints and resource availability. The bifurcation diagram is drawn for the Logistic map that presents the phenomena inside the chaotic region.

Biofertilizer based on <i>Agrobacterium </i>as a key to food security

Background: The concept of food security is contingent upon the fulfillment of two fundamental requirements: physiological and socioeconomic. The former comprises providing sustenance that is both safeguarded and enhanced in line with people’s nutritional needs and priorities, whereas the latter includes the mechanisms by which these needs are supplied. The objective is to ensure a state of robust and healthy well-being. As a sustainable solution, biofertilizers play a pivotal role in addressing the challenges of food security. Biofertilizers represent a cost-effective and environmentally friendly solution, with the potential to enhance soil productivity through nitrogen fixation. They also enhance crop yield by increasing the concentration of nutrients. Access to functional foods derived from biofertilizer-enhanced yields may contribute to improved dietary diversification and overall well-being. Objective: The objective is to isolate and screen the most active nitrogen-fixing bacterium as a basis to a new biofertilizer. Methods: The isolation of nitrogen-fixing bacteria was conducted using the soil sowing technique. The selection of nitrogen-fixing bacteria was based on their morphophysiological characteristics. Bacterial growth was evaluated by viable cell count. Cultivation of the selected bacterium occurred in both flasks (on a shaker) and a bioreactor to compare growth conditions. The stimulatory effect of the selected bacterium on seed germination was assessed based on the final germination rate. The selected bacterium identified through molecular taxonomy. Results: A total of 100 pure cultures were isolated, from which nitrogen-fixing bacteria were selected. The cultivation conditions for these bacteria were optimized regarding pH, temperature and process duration in a flask on a shaker. Strain NB4 exhibited the most favorable development under optimal settings. Additionally, cultivation parameters for this strain were optimized in a laboratory bioreactor. Notably, a bacterial liquid culture water solution comprising 1.5% strain NB4 facilitated complete germination of wheat (Triticum aestivum L.), seeds and produced high-quality sprouts. The 16S rRNA gene sequence of strain NB4 was submitted to the GenBank database under accession number MT670424.1, identifying it as Agrobacterium Pusense RP 1. Conclusion: This research aimed to develop an effective biofertilizer to tackle the pressing issue of food security. The project’s cornerstone was Agrobacterium pusense RP 1, nitrogen-fixing strain isolated and identified through rigorous research. Keywords: Isolation and identification of nitrogen-fixing bacteria, cultivation in bioreactor, germination of wheat seeds, Agrobacterium pusense.

Impact of Agroforestry Practices on Soil Microbial Diversity and Nutrient Cycling in Atlantic Rainforest Cocoa Systems

Microorganisms are critical indicators of soil quality due to their essential role in maintaining ecosystem services. However, anthropogenic activities can disrupt the vital metabolic functions of these microorganisms. Considering that soil biology is often underestimated and traditional assessment methods do not capture its complexity, molecular methods can be used to assess soil health more effectively. This study aimed to identify the changes in soil microbial diversity and activity under different cocoa agroforestry systems, specially focusing on taxa and functions associated to carbon and nitrogen cycling. Soils from three different cocoa agroforestry systems, including a newly established agroforestry with green fertilization (GF), rubber (Hevea brasiliensis)–cocoa intercropping (RC), and cocoa plantations under Cabruca (cultivated under the shave of native forest) (CAB) were analyzed and compared using metagenomic and metaproteomic approaches. Samples from surrounding native forest and pasture were used in the comparison, representing natural and anthropomorphic ecosystems. Metagenomic analysis revealed a significant increase in Proteobacteria and Basidiomycota and the genes associated with dissimilatory nitrate reduction in the RC and CAB areas. The green fertilization area showed increased nitrogen cycling activity, demonstrating the success of the practice. In addition, metaproteomic analyses detected enzymes such as dehydrogenases in RC and native forest soils, indicating higher metabolic activity in these soils. These findings underscore the importance of soil management strategies to enhance soil productivity, diversity, and overall soil health. Molecular tools are useful to demonstrate how changes in agricultural practices directly influence the microbial community, affecting soil health.

Adaptive constraint-guided surrogate enhanced evolutionary algorithm for horizontal well placement optimization in oil reservoir

In the face of escalating global energy demands, this study introduces an Adaptive Constraint-Guided Surrogate Enhanced Evolutionary Algorithm (ACG-EBS) for optimizing horizontal well placements in oil reservoirs. Addressing the complex challenge of maximizing oil production, the ACG-EBS integrates geological, engineering, and economic considerations into a novel optimization framework. This algorithm stands out for its adept navigation through a complex and discrete decision space of horizontal well placements, an area where traditional methods often encounter challenges. Key innovations include the Adaptive Constraint Initialization Mechanism (ACIM) and the Evolutionary Constraint-Tailored Candidate Refinement strategy (ECTCR), which collectively elevate the feasibility of candidate solutions. An enhanced balance strategy harmonizes comprehensive and niche surrogate models, optimizing the balance between exploration and exploitation. Through testing on both two-dimensional and three-dimensional reservoir models, the ACG-EBS has proven highly effective in identifying optimal well placements that align with field deployment realities and maximize economic returns. This contribution significantly supports the ongoing evolution of oilfield development optimization, showcasing the algorithm's potential to enhance oil production and economic outcomes.

Effect evaluation of fluid movement and rock properties for artificial seismic activity on hydrocarbons

Despite the effectiveness of seismic stimulation in enhancing oil production from reservoirs, the impact of high-frequency vibrations on oil droplets confined within pore throats has not been adequately investigated. This laboratory-scale experimental study examines the impact of low and high-frequency sinusoidal vibrations in dislodging oil droplets trapped in a specific pore-throat region. Sinusoidal vibrations ranging from 10 to 80 Hz and with maximum displacement amplitudes of 1.2–0.06 mm are applied. By comparing the images captured prior to and after the application of seismic vibrations, the amount of oil recovered is determined. Commercial gasoline and diesel are used as trapped oil samples, and water is used as the injection fluid to bring out the effect of fluid viscosities in seismic dislodgment. While applying vibrations to trapped oil in the pore throat, three different recovery modes are observed: continuous, snap-off, and emulsified. The continuous oil recovery mode is observed in cases with minimal flow resistance through the pore throat, whereas a snap-off or intermittent recovery mode is observed when the flow resistance is high, and the vibration frequencies fall within the midrange of 40-60 Hz. An emulsified oil recovery mode is observed at high vibration frequencies. The amount of recovered oil increases as geometrical restrictions and trapped oil viscosity decrease. Seismic mobilization is observed to be directly proportional to the mobilization velocity and inversely proportional to the entrapped oil viscosity and geometrical restriction factors.

Techno-economic-environmental study of CO2 and aqueous formate solution injection for geologic carbon storage and enhanced oil recovery

As carbon capture, utilization, and storage (CCUS), carbon-dioxide enhanced oil recovery (CO2 EOR) has inherent shortcomings, such as inefficient oil recovery and carbon storage, and low storage security with mobile CO2. This paper presents a techno-economic-environmental analysis of using formate species, a product of CO2 electrochemical reduction, as an alternative carbon carrier for sequestration and EOR in a carbonate oil reservoir in the Gulf of Mexico Basin. CO2 injection, water-alternating-CO2 injection, and aqueous formate solution injection were compared using a compositional reservoir simulation model and an economic calculator. Formate solution injection yielded greater levels of oil recovery and net carbon storage, where the carbon-bearing species resided in the dense aqueous phase without having to rely on petrophysical trapping mechanisms (structural and capillary). The enhanced oil production, net carbon storage, and storage security can be promoted by providing formate-based CCUS with more incentives (e.g., greater tax credit) in comparison to CO2-based CCUS for EOR and the manufacture of chemicals and products. In establishing carbon storage incentive policies and regulations, policymakers should include alternative carbon carriers.

Physico-chemical Characterization and Taxonomic Classification of Soil Profiles in a Toposequence Located in RRTTS and KVK Farm, Keonjhar, Odisha, India

The study investigates the physico-chemical characteristics and taxonomic classification of soil profiles along a toposequence at the RRTTS and KVK farm, Keonjhar, Odisha. Three distinct land types - upland, medium land, and lowland - were selected for the study, representing varying topographic positions. The investigation focused on soil properties such as bulk density, particle density, pH, organic carbon content, electrical conductivity, cation exchange capacity (CEC), base saturation, and available macro and micronutrients. Results indicated that bulk and particle densities were lower in upper horizons and increased with depth, while soil pH exhibited an increasing trend with increasing depth, likely due to the movement of basic cations during intensive rainfall. Organic carbon content was higher in surface horizons and declined with depth, whereas available potassium increased with depth, attributed to parent material and clay content. The exchangeable cations, primarily calcium and magnesium, dominated the soil profiles. The soils were classified into Loamy-skeletal, mixed, hyperthermic Typic Ustorthents (Pedon 1), Fine-loamy, mixed, hyperthermic Udic Haplustalfs (Pedon 2), and Fine-loamy, mixed, hyperthermic Udic Paleustalfs (Pedon 3). The study concluded that different landforms within the toposequence require specific land-use planning and conservation measures to enhance soil productivity and sustainability. Upland areas are recommended for plantation and agroforestry, medium land for crop production, and low land for paddy cultivation and pisciculture. Tailored conservation strategies, including contour cultivation and water harvesting, are essential to mitigate soil erosion and optimize land use in the region.

Enhancing oil production via radical reactions during hydrothermal coliquefaction of biomass model compounds and plastics: A molecular dynamic simulation study

Recently, hydrothermal coliquefaction of biomass and plastic waste has attracted considerable research interest. However, there is a notable gap in understanding the fundamental reaction mechanisms between biomass and plastics during coliquefaction. This study focused on the coliquefaction of biomass model compounds and plastic polymers using ReaxFF molecular dynamics simulations under both subcritical and supercritical water conditions. Molecular-level tracking and probing of the reaction mechanisms between biomass model compounds and plastics were conducted to purposefully enhance oil production. The study observed related radical reactions between by-product molecules, with detailed mechanisms primarily involving (1) ▪OH radicals released by aqueous phase molecules from biomolecules, transferring as H2O molecules and facilitating plastic depolymerization, and (2) C1–C4 radicals in the gaseous phase, emitted from biomolecule and plastic, colliding and subsequently recombining to form oil molecules. Moreover, the yield of multiple products from various mixtures were evaluated by considering the key reaction parameters including reaction temperature and feedstock blended ratio. An exploration into the effect of coliquefaction on oil yield was conducted to precisely identify the optimal coliquefaction conditions. The positive effect of coliquefaction was more pronounced between biomass model compounds and aromatic polymers compared to aliphatic polymers. Analysis of reaction mechanisms and product outcomes has shown that hydrothermal coliquefaction is a viable approach to improving oil production from multi-source organic solid waste.

Reducing the uncertainty in estimating soil microbial-derived carbon storage

Soil organic carbon (SOC) is the largest carbon pool in terrestrial ecosystems and plays a crucial role in mitigating climate change and enhancing soil productivity. Microbial-derived carbon (MDC) is the main component of the persistent SOC pool. However, current formulas used to estimate the proportional contribution of MDC are plagued by uncertainties due to limited sample sizes and the neglect of bacterial group composition effects. Here, we compiled the comprehensive global dataset and employed machine learning approaches to refine our quantitative understanding of MDC contributions to total carbon storage. Our efforts resulted in a reduction in the relative standard errors in prevailing estimations by an average of 71% and minimized the effect of global variations in bacterial group compositions on estimating MDC. Our estimation indicates that MDC contributes approximately 758 Pg, representing approximately 40% of the global soil carbon stock. Our study updated the formulas of MDC estimation with improving the accuracy and preserving simplicity and practicality. Given the unique biochemistry and functioning of the MDC pool, our study has direct implications for modeling efforts and predicting the land-atmosphere carbon balance under current and future climate scenarios.

Enhancing Oil Production Rate by Well Type Conversion in an Iraqi Field

Horizontal wells have been drilled worldwide for the past decades, mainly to increase well’s deliverability. Many vertical wells have been converted to horizontal wells. Only some of them were successful in increasing the oil production rate as expected. In this study, a vertical well (V1) in Kirkuk field was studied and converted to a designed horizontal well (H1) to increase the productivity. PROSPER software was used to model both wells. H1 was designed with well horizontal lengths of 152, 305, 457, and 610 m, and permeability ratios of 0.1, 0.2, 0.4, 0.7 and 1.0. A developed correlation for calculating well construction cost, along with Questor software, were used to perform the economic analysis. It was found that the highest productivity index and production rate ratios were 5.2 and 2.41, respectively. Reservoir pay thickness and permeability ratio are the main parameters in determining the minimum feasible horizontal well length. Reservoir pressure and water cut were found to be the most sensitive parameters in both wells. The net profit generated by a horizontal well with length of 610 m and permeability ratio of 0.2 is 1.9 folds the net profit generated by a vertical well, in three years.

Exploring fatty acid composition, bioactive compounds, and antioxidant properties in oils of newly developed sesame mutant lines in Morocco

AbstractSesame (Sesamum indicum L.) is renowned for its significance as a global oilseed crop, valued for its high oil content and nutritional properties. This study aimed to explore the fatty acid composition, bioactive compounds, and antioxidant attributes of sesame mutant oils, examining their potential applications in food industry. Nine M4 mutants, along with their parents, were grown in two contrasting environments (Taoujdate and Afourare) to investigate their seed oil, phenolic and flavonoid contents, the balance between omega‐6, omega‐9, and omega‐3 fatty acids, iodine value, and susceptibility to oxidation. Genotype and environment main effects as well as their interaction had a significant effect on the majority of the parameters studied. The mutant “US2‐1” stands out with a distinctive fatty acid profile, featuring the highest saturated fatty acids, ω‐6/ω‐9 ratio, and omega‐3 content, in addition to its high total flavonoid content and remarkable oxidative stability. “ML2‐10,” “US1‐2,” “US2‐6,” and “US2‐7” exhibit high oil content, coupled with substantial levels of phenols and flavonoids, rendering them excellent candidates for culinary and industrial applications where oxidative stability is important. “ML2‐68,” “ML2‐72,” “US06,” “US1‐DL,” and “US1‐3” offer versatile options with their moderate oil content and fatty acid profiles that resist oxidation. This research highlights the potential for breeding sesame mutants tailored to specific applications, contributing to both enhanced oil production and improved nutritional value. The insights gained here pave the way for the development of sesame varieties with superior nutritional and functional attributes, thereby promoting the sustainable production and consumption of sesame oil.

A novel hybrid enhanced oil recovery technique to enhance oil production from oil-wet carbonate reservoirs by combining electrical heating with nanofluid flooding

Enhanced Oil Recovery provides a promising technique to maximise fossil fuel recovery from existing resources, and when used in conjunction with Carbon Capture and Storage/Utilisation provides a way to support a transition to alternative cleaner fuels. A hybrid Enhanced Oil Recovery method by a combination of electrical heating and nanofluid flooding was applied to oil-wet carbonate reservoirs and assessed in terms of the oil production, zeta potential, contact angle, pellet compaction, interfacial tension, and pH values. The hybrid technique consisted of a combination of direct current (up to 30 V) and iron oxide (Fe2O3) or magnesium oxide (MgO) nanofluids. Both nanofluids were injected into oil-wet Austin chalk – our laboratory model of an oil-wet carbonate reservoir – and then electrical heating was started, or vice versa. Introducing electrical heating first increased oil recovery by up to 27% in seawater compared to 16% in deionised water. When Fe2O3 nanofluid was injected, oil recovery further increased to 32% in seawater and 24% in deionised water. The contact angle and zeta potential decreased from 124° to 36° and from −24.4 to −23.7 mV, respectively, when nanofluid was injected in seawater, leading to better nanofluid stability and penetration into the carbonate rock as shown by increased pellet porosity from 6.6% to 14.8%. Moreover, it was found that the interfacial tension was reduced from 72 to 32.7 mN/m in the pre-magnetised samples with Fe2O3 NPs injection compared to 33.2 mN/m in the samples with MgO injection. It was found from our experiments that the effect of the generated electricity on the surface charge was of a temporary nature as the zeta potential of the rock returned to its original value as soon as the power was disconnected. The mechanism underlying the hybrid Enhanced Oil Recovery EOR technique from the laboratory findings was found to be based on electrowetting and nanofluid adsorption. Results indicate that the technique is promising for further improving oil recovery and securing energy supply during the transition to net zero.

Dispersion of polyacrylamide and graphene oxide nano-sheets for enhanced oil recovery

Hydrolysed polyacrylamide (HPAM) is widely used in enhancing oil production during tertiary flooding processes by improving the sweep efficiency . However, HPAM faces many challenges under high-temperature and high-salinity conditions mainly caused by the degradation. To overcome these challenges, incorporation of approprioate nanoparticles into HPAM solutions have been recently suggested to enhance its performance during the enhanced oil recovery (EOR) process. The current study specifically investigated the potential of amphiphilic graphene oxide (GO) in enhanicng the performance of HPMA. Its influences on HPAM in terms of the surface activity at the oil-water interface, the mobility behaviour, and the effectiveness in oil recovery were examined. The results revealed that adding up to 0.8 wt% of GO into HPAM reduced the oil-water interfacial tension (IFT) from 62.54 mN/m to 42.78 mN/m, and the contact angle (CA) from 71.08º to 68.84º, while in the mean time increasing the viscosity from 9.07 mPas to 16.49 mPas. Furthermore, the pilot core-flooding study demonstrated that with an addition of 0.8 wt% GO, HPAM achieved higher oil recovery rate (i.e., 76.83 %) than that of the pure HPAM (i.e., 67.39 %). The improved oil recovery performance was attributed to a better mobility ratio, resulting from the increased viscosity of the composite and reduced IFT, which was facilitated by the amphiphilic behaviour of GO, as supported by the desirability model.

Increasing productivity by using smart gas for optimal management of the gas lift process in a cluster of wells

In the face of the escalating global energy demand, the challenge lies in enhancing the extraction of oil from low-pressure underground reservoirs. The conventional artificial gas lift method is constrained by the limited availability of high-pressure gas for injection, which is essential for reducing hydrostatic bottom hole pressure and facilitating fluid transfer to the surface. This study proposes a novel ‘smart gas’ concept, which involves injecting a gas mixture with an optimized fraction of CO2 and N2 into each well. The research introduces a dual optimization strategy that not only determines the optimal gas composition but also allocates the limited available gas among wells to achieve multiple objectives. An extensive optimization process was conducted to identify the optimal gas injection rate for each well, considering the limited gas supply. The study examined the impact of reducing available gas from 20 to 10 MMSCFD and the implications of water production restrictions on oil recovery. The introduction of smart gas resulted in a 3.1% increase in overall oil production compared to using natural gas. The optimization of smart gas allocation proved effective in mitigating the decline in oil production, with a 25% reduction in gas supply leading to only a 10% decrease in oil output, and a 33% reduction resulting in a 26.8% decrease. The study demonstrates that the smart gas approach can significantly enhance oil production efficiency in low-pressure reservoirs, even with a substantial reduction in gas supply. It also shows that imposing water production limits has a minimal impact on oil production, highlighting the potential of smart gas in achieving environmentally sustainable oil extraction. Furthermore, the implementation of the smart gas approach aligns with global environmental goals by potentially reducing greenhouse gas emissions, thereby contributing to the broader objective of environmental sustainability in the energy sector.

The Production of Renewable Fuels Sago Dregs and Low-Density Polyethylene by Pyrolysis and its Characterization

Biomass has been suggested as a sustainable alternative to substitute fossil fuels. Based on the pyrolysis method, the biomass would be converted into energy through decomposition by thermal degradation under an inert atmosphere, resulting in charcoal, liquid, and gas products. The quality of oils is effectively enhanced through the pyrolysis of lignocellulosic biomass and plastic due to the facilitation of deoxygenation by plastics. This study investigates the impact of incorporating low-density polyethylene (LDPE) plastic in co-pyrolysis with sago dregs (SDs) waste. Pyrolysis of SDs and LDPE mixtures with ratios of 5:1, 4:2, 3:3, 2:4, and 1:5 at various temperatures of 375°C, 425°C, and 475°C. The maximum oil yield obtained for SDs and LDPE pyrolysis was 44.94%. The calorific value (CV) of all observed compositions is a minimum of 10,579.57 kcal kg-1 and a maximum of 11,545.21 kcal kg-1. The gas chromatography-mass spectroscopy (GC-MS) analysis confirmed the interaction between SDs and LDPE on co-pyrolysis. The addition of LDPE will produce rich aliphatic and aromatic compounds, like the proportions of alkanes (45.53%), alkenes (30.62%), alcohol (0.4%), and benzene (17.68%). Co-pyrolysis of SDs and LDPE promotes enhanced oil production by reducing oxygenated compounds and increasing hydrocarbon compounds.

Development of technology for intensification of oil production using emulsion based on natural gasoline and solutions of nitrite compounds

This article focuses on the issue of enhancing oil production by eliminating asphalt, resin, and paraffin deposits (ARPD). These deposits pose significant challenges, including equipment clogging, reduced well productivity, and increased maintenance costs. Moreover, paraffin deposits can damage well equipment, cause accidents, and halt hydrocarbon production. The study involved laboratory and field experiments at the Uzen field to evaluate the efficiency of removing and dissolving paraffin using an emulsion composed of gas gasoline and nitrite compound solutions. Previous studies conducted at NGDU Uzenneft were critically analyzed for comparison. The scientific innovation of this research lies in the development of an emulsion based on gas gasoline and nitrite compound solutions to remove ARPD. The composition was designed to exclude highly aggressive components. It utilized a previously developed emulsion base and incorporated ammonium nitrite, slightly acidified with hydrogen chloride (0.1% by mass), to promote an exothermic reaction.The effectiveness of this technology was measured by changes in daily oil production rates, the duration of the treatment's effect, and changes in the well productivity coefficient before and after treatment.Results indicate that the developed technology successfully removed paraffin from the bottomhole zone of oil wells and increased oil production in 5 out of 6 wells at the Uzen field. The positive effect lasted 17-27 days, with oil inflow increasing by 17-174%. This led to a total additional oil production of 1528 tons from the five wells. Keywords: bottomhole formation zone; asphalt-resin-paraffin deposits; nitrite composition; surfactants; enhanced oil recovery.

Shifts in the nitrogen cycle under different fertilizer management practices

Human population is dependent on agricultural production, but these activities pose multiple threats to soil health and indirectly to ecological sustainability. Synthesis of fertilizers proved to be a miraculous solution to enhance soil productivity, but this advancement came with many unseen risks. Long-term research stations that have decades long experiments with fertilizers additions are paramount in better understanding long-term impact of fertilizer use. Our study focused on ammonium and nitrate levels found in soils in an experiment of inorganic nitrogen addition than began in 1975. We further directed our attention to soil mineralization potential, nitrate reductase activities and densities of two major microbial functional groups: ammonifiers and denitrifiers. Our data suggests that ammonium has a stronger tendency of soil buildup than nitrate and that increased levels of inorganic nitrogen species also impacted molecular compartments and processes such as mineralization potential, soil microbiota and enzymatic activities. Another result indicates that analysed soils reached a storage limit for phosphorus which threatens to overburden other ecosystems.

Insight into the Imbibition Behavior of Low-Frequency Artificial Vibration Stimulation in Tight Sandstone.

Spontaneous imbibition is the primary mechanism responsible for the enhanced oil production in a tight reservoir after hydraulic fracturing. In this article, a low-frequency artificial vibration physics stimulation method was employed to evaluate the effect of low-frequency vibration on imbibition recovery in tight sandstones. Furthermore, a high-precision in situ computed tomography (CT) scan was employed to investigate the effect of low-frequency vibration on the distribution of remaining oil micro-occurrence dynamic alterations in pore space. The findings of the study show that (1) low-frequency artificial physical vibration stimulation has been found to be highly effective in enhancing imbibition recovery in tight sandstone. The sensitivity of the vibration parameters on imbibition recovery from highest to lowest is vibration frequency, vibration intensity, and vibration time. The optimum vibration parameters for this process are a vibration frequency of 30 Hz, a vibration intensity of 2.0 m/s2, and a vibration time of 30 h. (2) Under the optimum low-frequency vibration, the imbibition recovery of tight sandstone with various physical properties can reach between 13.6 and 28.3%. This is remarkably higher than the spontaneous imbibition recovery, which ranges from 9.4 to 17.1%. Additionally, core samples with higher permeability and better pore structure show a more significant increase in imbibition recovery under the vibration treatment. Furthermore, low-frequency vibration stimulation effectively shortens the imbibition completion time, reducing the completion time from 81 h to approximately 55 h. (3) After the spontaneous imbibition process, the initial continuous oil phase present in the pore space is dispersed by the water phase imbibition process. The remaining oil is dominant in the form of a network type, which is concentrated in the central pore space area of the core. Low-frequency vibration treatment can effectively promote a positive imbibition process. The network remaining oil saturation in the core can be further dispersed, especially closer to the surface of the core area after frequency vibration treatment. Then, the cluster remaining oil type with a more dispersed and simpler individual structure has become the new dominant remaining oil micro-occurrence form in the pore space. The findings of this research investigate a novel technological approach to enhance the imbibition efficiency of a tight sandstone reservoir.

Constraint optimization of an integrated production model utilizing history matching and production forecast uncertainty through the ensemble Kalman filter

The calibration of reservoir models using production data can enhance the reliability of predictions. However, history matching often leads to only a few matched models, and the original geological interpretation is not always preserved. Therefore, there is a need for stochastic methodologies for history matching. The Ensemble Kalman Filter (EnKF) is a well-known Monte Carlo method that updates reservoir models in real time. When new production data becomes available, the ensemble of models is updated accordingly. The initial ensemble is created using the prior model, and the posterior probability function is sampled through a series of updates. In this study, EnKF was employed to evaluate the uncertainty of production forecasts for a specific development plan and to match historical data to a real field reservoir model. This study represents the first attempt to combine EnKF with an integrated model that includes a genuine oil reservoir, actual production wells, a surface choke, a surface pipeline, a separator, and a PID pressure controller. The research optimized a real integrated production system, considering the constraint that there should be no slug flow at the inlet of the separator. The objective function was to maximize the net present value (NPV). Geological data was used to model uncertainty using Sequential Gaussian Simulation. Porosity scenarios were generated, and conditioning the porosity to well data yielded improved results. Ensembles were employed to balance accuracy and efficiency, demonstrating a reduction in porosity uncertainty due to production data. This study revealed that utilizing a PID pressure controller for the production separator can enhance oil production by 59% over 20 years, resulting in the generation of 2.97 million barrels of surplus oil in the field and significant economic gains.

Predicting Oil Production After Enhancement Techniques Using Multidimensional Feature Representation Learning: A Case Study of Profile Control Technique

Summary The prediction of oil production following enhancement techniques has garnered widespread attention, leading scientists to explore this area using machine learning. However, field data collection constraints and single model accuracy limitations mean few models can precisely predict daily oil production after technique implementation. Building upon previous research, this paper introduces a model that predicts oil production after enhancement operations, utilizing multidimensional feature representation learning. It thoroughly examines three characteristic categories affecting the effectiveness of oil production enhancement techniques: geological static parameters, production dynamic parameters, and enhancement technique process parameters. The model comprehensively explores these features with an emphasis on global spatial, local spatial, and temporal information. A complete machine learning prediction process is established, which includes data preprocessing, model training, cross-validation, and oil production prediction after implementing enhancement techniques. The first part of the model involves representation learning on processed data, producing three sets of new features: global spatial, local spatial, and temporal information. These features are fused with the original data, serving as input for the advanced ensemble learning model XGBoost, which predicts daily oil production after implementing the technique. Following the construction of the model, actual field data from profile control techniques are selected to conduct various evaluations based on the model’s performance on validation and test sets. Compared with traditional machine learning regression algorithms, this model demonstrates significantly higher predictive accuracy. The prediction accuracy for oil production using given enhanced techniques reached 96% in the validation set and 94% in the test set. This research provides a technical foundation for selecting appropriate production enhancement techniques in oil fields by accurately predicting oil production after implementing enhancement techniques, which offers guidance for actual oilfield production.