Oil Production Research Articles

Determination of Carotenoid Bioavailability from Palm Oil Microencapsulation

Indonesia is the largest palm oil supplier in the world with a total production value of 20.97 million tons. Palm oil has a high content of carotenoids that act as antioxidants in the body. However, carotenoids and their derivatives have a conjugated structure that is unstable to oxidation and easily damaged. One of the optimal efforts to maintain the stability of carotenoids is by microencapsulation. This study aims to determine the efficiency of the palm oil microencapsulation method in maintaining the carotenoid components in it. The method used in this research is Systematic Literature Review based on Google Scholar, ScienceDirect, and Springer databases with predetermined inclusion criteria. The results showed that all palm oil microencapsulation methods produced good efficiency values and stable physicochemical characteristics of carotenoids even including other micronutrients such as vitamin E, moisture content, fatty acids, etc. which were also classified as stable. Overall, the supercritical carbon dioxide (SEDS) method produced the best quality while the spray drying method is a good choice for commercial microencapsulation. The conclusion of this study is that microencapsulation is able to protect the bioavailability of carotenoids in palm oil in a stable condition with values that are still within the standard range so as to produce better palm oil products as food ingredients for further use in a food product

Unveiling the Mysteries of Fractured Basement Oil Residues in the Upper Benue Trough, Nigeria

This study offers additional evidence for the occurrence of oil residues within fractures of the basement rocks in the Upper Benue Trough, Nigeria. The data suggests that the observed oil residues were originally generated as light oils, which were later biodegraded into heavy oils. These Upper Benue Trough's oil stains are a valuable tool for hydrocarbon exploration in the region as they indicate the existence of a petroleum system in the basin. We find a strong similarity to the proportions of C27, C28, and C29 regular steranes of oils found in the sandstones and shales of the Bima Formation in the Upper Benue Trough when we plot the relative quantities of these steranes of the investigated basement rock oil types on a ternary graph. This shows a positive correlation between the oils from the Bima Formation and the fractures found in the Precambrian basement rocks. Additionally, the studied basement oils and the oils extracted from the Bima Formation had comparable sterane maturity criteria. Again, trisnorhopane thermal indicators are also identical in the studied oils. The C3222S/(22R+22S) homohopane isomerization ratio and Ts: Tm ratio of the examined basement rock oils are similar to those of the oils extracted from the Bima Formation's shales, suggesting that the Bima Formation's shale is the primary source rock for the examined basement rock oils. Oils have also been reported to develop similarly in the Precambrian basement rocks of the Bongar Basin in the Chad Republic, known as basement-buried hills. As members of the West African rift basins, the Nigerian Upper Benue Trough and the Bongar Basin share genetic ancestry. As a result, we should be looking for exploratory opportunities that mimic the Bongor Basin's basement buried hills, which are currently the location of commercial oil production.

A Comprehensive Methodology for Image Recognition Utilizing Machine Learning and Computer Vision: Automation of the Harvesting Process

This study aims to investigate the machine learning techniques implemented in image recognition technology for the identification and classification of oil palm fruit ripeness. The accurate determination of fruit ripeness is crucial for optimizing harvest time and improving oil yield. The palm oil industry is one of the major plantations in Malaysia. The harvesting process of oil palm fruit was conducted with traditional methods by relying on manual inspection, which can be subjective and inconsistent. Plus, it required several workers. A model of image recognition was developed using machine learning algorithms and computer vision to automate the harvesting process and overcome the shortage of labor issues. Implementing this technology in the field could lead to more consistent harvests and higher-quality oil production. Several machine learning models were developed, trained, and tested for their ability to classify the ripeness stages. The findings suggest the trending techniques in implementing image recognition which can provide a reliable and efficient tool for assessing oil palm fruit ripeness.

Influences of the stress ratio and local micro mineral aggregates on small fatigue crack propagation in the shale containing bedding planes

Due to the existence of bedding planes in shale oil reservoirs, the complexity of crack networks created by conventional hydraulic fracturing (HF) technology is limited, resulting in low oil production. In this paper, a fatigue loading method was proposed to increase the complexity of the cracking network. The propagation behaviors of small cracks were investigated and compared under both monotonic and fatigue loading conditions by using SEM in-situ three-point bending tests. In addition, the influences of local micro mineral aggregates and stress ratios (R = 0.1, 0.3 and 0.5) on the propagation behavior of small fatigue cracks (SFCs) in shale were quantitatively evaluated. The SEM in-situ fatigue tests demonstrated the effectiveness of fatigue loading in enabling SFC to propagate through the bedding plane and increase crack network complexity from a micro perspective. A fitting exponential formula of the stress intensity factor range threshold ΔKth and stress ratio R was obtained. This study assists us in deeply understanding the influence of micro mineral aggregates and stress ratio on the SFC propagation mechanism and its implications for HF design in shale oil reservoirs.

Electro-sorption/-desorption with bio-sourced granular activated carbon electrode for phenols recovery and combination with advanced electro-oxidation for residual olive mill wastewater treatment

To face the releasing of hazardous solid and liquid wastes into the environment from the olive oil production industry, it is newly proposed a circular economy approach by implementing electro-sorption of value-added phenolic compounds (PCs) followed by electro-desorption using a bio-sourced granular activated carbon (GAC) electrode made of olive pomace waste. The remaining organic compounds present in the real olive mill wastewater (OMWW) were treated by advanced electrooxidation.The PCs electro-sorption study highlighted efficiency around 72 % in synthetic matrix against 68 % in real effluents, whose electro-sorption capacities could be partly attributed to the high electroactive surface area (7.8 × 103 cm2), high exchange current intensity (I0) value (5.5 × 10−3 A), and low charge transfer resistance (RCT) value (4 Ω) compared to the literature. The study further emphasized the fact that the electro-sorption selectivity was not only dependent on pKa of PCs with respect to solution pH, but also on the size of adsorbed molecules relative to the pore size distribution of GAC. The maximal percentage of PCs recovered from GAC after electro-desorption experiments was 34.5 %, while the global chemical oxygen demand (COD) removal efficiency was 92 % of the pre-filtered real effluent at the cost of scaling during advanced electrooxidation of residual OMWW.

Seasonal Dynamics of Caligus clemensi Infestation in European Seabass and Flathead Grey Mullet Integrating Morphological, Molecular, Immunological, and Environmental Perspectives

This case study investigates the seasonal prevalence, morphological characteristics, molecular identity, host immune response, and environmental factors influencing Caligus clemensi infestations in farmed European seabass and flathead grey mullet at a single marine fish farm. A total of 600 fish (400 seabass, 200 mullet) were examined over one year, revealing seasonal fluctuations in parasite prevalence and intensity. C. clemensi infestation peaked in winter for seabass (75% prevalence) and spring for grey mullet (80% prevalence), with notable declines in summer and autumn for both species. Morphological analysis confirmed C. clemensi as the causative agent, exhibiting sexual dimorphism and characteristic features including a quadrilateral cephalothorax and disk-shaped lunules. Molecular characterization of the 18S rRNA gene corroborated the morphological identification, with phylogenetic analysis revealing a well-supported monophyletic clade for C. clemensi within the family Caligidae. Quantitative real-time PCR demonstrated significantly elevated interleukin-1β (IL-1β) expression in infected fish, indicating a robust inflammatory response. Grey mullet and seabass exhibited high IL-1β upregulation. Histopathological examination revealed severe gill tissue damage, vascular changes, and hepatic steatosis in infected fish. Water quality analysis identified several parameters exceeding permissible limits, including total suspended solids (4800-5100 mg/L), total dissolved solids (32000 mg/L), sulfates (2300 mg/L), and chlorides (18000 mg/L). These elevated levels, likely associated with nearby oil production and refining activities, created conditions conducive to parasite proliferation. The high total suspended solids might provide substrates for C. clemensi settlement and attachment, while increased dissolved ions could stress fish and reduce their parasite resistance. This multidisciplinary case study revealed complex host-parasite interactions between C. clemensi and farmed marine fish, highlighting the need for improved water quality and targeted parasite control to enhance aquaculture sustainability in the Suez Canal region.

The Future of Phosphoric Acid Production -Why We Have to Leave Trodden Paths.

This paper examines the need for innovation in phosphorus fertilizer production. An important area requiring action is the use of sulfuric acid in the wet chemical process (WCP), which is the dominant process in phosphate fertilizer production. About 50 % of the sulfuric acid produced worldwide is used for fertilizers, and ~95 % of the world's fertilizers are based on sulfuric acid. The latter is almost exclusively a by-product of gas and oil production, so the production of conventional P fertilizer is largely dependent on the availability of oil and gas. In addition to rendering P fertilizer production independent of fossil raw materials, energy consumption, CO2 emissions, phosphogypsum production and water consumption should also be considered. With the example of the PARFORCE process and the Improved Hard Process (IHP), new non-sulfuric acid-based alternatives are discussed with respect to overcoming the drawbacks of the classical WCP by being completely independent of fossil sources, working with renewable energies as the sole energy source, and the option of using seawater instead of fresh water. These new processes adhere to the principles of climate neutrality, zero waste production, low CO2 footprint, water conservation, renewable energy use, and energy and resource efficiency. This demonstrates what sustainable innovation can look like from a production perspective. The discussion will focus on whether current incentives are sufficient to realize the sustainability innovations discussed.

Development of a Multi-Source Satellite Fusion Method for XCH4 Product Generation in Oil and Gas Production Areas

Methane (CH4) is the second-largest greenhouse gas contributing to global climate warming. As of 2022, methane emissions from the oil and gas industry amounted to 3.586 million tons, representing 13.24% of total methane emissions and ranking second among all methane emission sources. To effectively control methane emissions in oilfield regions, this study proposes a multi-source remote sensing data fusion method based on the concept of data fusion, targeting high-emission areas such as oil and gas fields. The aim is to construct an XCH4 remote sensing dataset that meets the requirements for high resolution, wide coverage, and high accuracy. Initially, XCH4 data products from the GOSAT satellite and the TROPOMI sensor are matched both spatially and temporally. Subsequently, variables such as longitude, latitude, aerosol optical depth, surface albedo, digital elevation model (DEM), and month are incorporated. Using a local random forest (LRF) model for fusion, the resulting product combines the high accuracy of GOSAT data with the wide coverage of TROPOMI data. On this basis, ΔXCH4 is derived using GF-5. Combined with the GFEI prior emission inventory, the high-precision fusion dataset output by the LRF model is redistributed grid by grid in oilfield areas, producing a 1 km resolution XCH4 grid product, thereby constructing a high-precision, high-resolution dataset for oilfield regions. Finally, the challenges that emerged from the study were discussed and summarized, and it was envisioned that, in the future, with the advancement of satellite technology and algorithms, it would be possible to obtain more accurate and high-resolution datasets of methane concentration and apply such datasets to a wide range of fields, with the expectation that significant contributions could be made to reducing methane emissions and combating climate change.

Reductive Depolymerization of Lignin to Aromatic Compounds over Promoted Nickel Catalysts in Sub‐ and Supercritical Methanol

The use of γ‐Al2O3‐supported Ni catalysts promoted with either Cu or Fe was investigated for the reductive catalytic fractionation (RCF) of hybrid poplar in methanol at 200 and 250 °C. The effectiveness of lignin depolymerization was quantified in terms of the lignin oil production, the quantity and distribution of identifiable monomers present in the lignin oil, and the yield of residual solids. All of the Ni‐based catalysts tested provided improved yields of lignin oil and monomers, along with reduced char formation, relative to blank (sans catalyst) runs. The highest monomer yield of 51% was obtained at 250 °C over a 20 wt.% Ni‐5 wt.% Cu/Al2O3 catalyst, the improved performance obtained through Cu promotion being attributed to the ability of Cu to facilitate NiO reduction, resulting in an increased amount of Ni0 on the catalyst surface and, consequently, improved hydrogenation activity. The main monomers formed were propanol‐, propyl‐ and propenyl‐substituted guaiacol and syringol, the S/G ratio of the products corresponding closely to that in the native lignin.

Mathematical model of the system performance mode for simultaneous separate well operation

Relevance. The trend of oil production technology development is related to many relevant topics. One of such actual directions is the technology of simultaneous separate well operation, in particular, including two electric centrifugal pumps and double-sided submersible electric motor. The presence of two formations at the bottomhole implies the selection of the optimal layout, technological parameters of pumps pumping oil. Considering production from two independent formations in the well according to the mentioned technology, there is a high need in selection of correct parameters of installations at the design stage. In the absence of correct selection of technological parameters of units at the design stage, further operation of a well with two independent formations can be economically inexpedient, and in some cases unrealizable, which is due to a number of reasons. First, if the necessary underbalance is not provided for each particular formation, counterflow of fluid may occur and one of the pumps will not participate in the production process. Secondly, when operating an arrangement, which capacity significantly exceeds the capacity (fluid flow from the reservoir) of the well, there is a possibility of pumping failure and, as a consequence, there is a risk of potential failure. In this regard, an extremely urgent task at the moment is to ensure correct selection of technological parameters of electric centrifugal pump units used in simultaneous separate operation of wells with two independent formations. Aim. Development of a mathematical model that allows selecting the optimal technological parameters of the arrangement consisting of two electric centrifugal pumps and a double-sided submersible motor, used for simultaneous separate operation of wells with two independent formations. Methods. Numerical simulation methods for analyzing the operation mode of electric centrifugal pumps in conditions of oil production from two independent reservoirs. Results and conclusions. It was obtained that the developed mathematical model of the system operation mode for simultaneous separate operation of wells allows to estimate the potential of each individual selected pump during oil production (in time dynamics) by analyzing the depression on each individual reservoir, as well as modeling the process taking into account the potential backflow of liquid and supply failure.

Rankings of Shorelines of Georgian Black Sea Sector According to the Ecological Sensitivity Index (ESI)

Georgia is concidered as one of the best alternative transit countries connecting Asia and Europe. The transportation of oil and oil products from the Caspian and Central Asian regions to European countries is especially significant. This boosts the country’s economy, but it also increases the risk of marine environment pollution from oil hydrocarbons. In response to the risk of oil hydrocarbon pollution, it is necessary to intensify preventive monitoring efforts. This includes assessing the extent of oil hydrocarbon contamination on shores, in coastal waters, and in bottom sediments, as well as identifying and classifying areas along the coastline that are most sensitive to pollution. The division of shorelines into sensitive areas is carried out according to the ecological sensitivity index ESI, wich contains a numeric or alpha-numeric coded description of the shoreline characteristics for each shoreline segment. According to the 10 levels of sesitivity against oil pollution, the shoreline segments are classified from "low" sensitivity ESI 1 to "very high" sensitivity ESI 10, respectively 10 main classes and up to 30 sub-classes are identified. In Georgia coastal area, for the 113 km section from Ganmukhuri to Sarpi, we have identified shoreline segments with 7 main classes and 9 sub-classes of sensitivity. Keywords: Black sea, Georgia, oil, sensitivity, rankings , pollution

Analysis of Stakeholder Discourses on Petroleum Exploration and Production in the Brazilian Equatorial Margin

The exploration and production (E&P) of oil and natural gas in the Brazilian Equatorial Margin, particularly at the Amazon River Mouth, has become a subject of intense national and international debate. This study analyzes public discourses related to those activities within the context of Brazil’s environmental commitments under the Paris Agreement. The analysis spans the period from President Lula da Silva’s third inauguration, in January 2023, to May 2024, focusing on political and economic approaches. The method involved systematic literature review, discourse analysis, and content analysis, using the Atlas TI software as a content analysis tool to manage, code and categorize textual data. The results show the predominance of the right to development, ecological modernization, and energy clout narratives. The common but differentiated responsibilities narrative is deeply rooted in these dominant narratives and undermines the opposition to oil production in the Brazilian Equatorial Margin. The analysis reveal the complexity of the discursive coalitions formed and simultaneously offers insights to help public policymakers balance economic development, energy security, and environmental sustainability.

Hydrophobic association supramolecular gel suitable for oil and gas drilling in fractured formation

Supramolecular gel can be used to seal fractures and pores in the formation during oil and gas drilling and production. In this study, a supramolecular gel plugging agent based on hydrophobic association was prepared by free radical polymerization of acrylamide, octadecyl methacrylate, sodium dodecyl sulfate and other monomers by micellar copolymerization. The forming time, rheology, swelling, mechanical properties and plugging properties of supramolecular gels were studied. The experimental results show that the formation time of supramolecular gel plugging agent is controllable, and it has excellent viscoelastic recovery ability in a certain range of shear strain and scanning frequency. When the compression amount is close to 88.3%, the compressive stress reaches 3.82 MPa. Meanwhile, the swelling performance of supramolecular gel was good, and the equilibrium swelling degree reached 22.1% after 188 min swelling in 15% NaCl brine solution. In 1% NaCl solution, the equilibrium swelling degree of supramolecular gel reached 32.5%. In addition, supramolecular gel has strong formation bonding ability, good plugging performance, plugging rate is greater than 95%, can effectively reduce the leakage and improve the plugging effect of low permeability layer. It is of reference and guiding significance for the long-term plugging of heterogeneous and malignant leakage formations.

Event Classification on Subsea Pipeline Inspection Data Using an Ensemble of Deep Learning Classifiers

Subsea pipelines are the backbone of the modern oil and gas industry, transporting a total of 28% of global oil production. Due to several factors, such as corrosion or deformations, the pipelines might degrade over time, which might lead to serious economic and environmental damages if not addressed promptly. Therefore, it is crucial to detect any serious damage to subsea pipelines before they cause dangerous catastrophes. Inspections of subsea pipelines are usually made using a Remote Operating Vehicle and the inspection data is usually processed manually, which is subject to human errors, and requires experienced Remote Operating Vehicle operators. It is thus necessary to automate the inspection process to enable more efficiency as well as reduce costs. Besides, it is recognised that specific challenges of noisy and low-quality inspection data arising from the underwater environment prevent the industry from taking full advantage of the recent development in the Artificial Intelligence field to the problem of subsea pipeline inspection. In this paper, we developed an ensemble of deep learning classifiers to further improve the performance of single deep learning models in classifying anomalous events on the subsea pipeline inspection data. The output of the proposed ensemble was combined based on a weighted combining method. The weights of base classifiers were found by minimising the difference between the weighted combining result and the given associated ground truth annotation information. Three inspection datasets, gathered from different oil and gas companies in the United Kingdom, were analysed. These datasets were recorded under varying conditions and include a range of anomalies. The results showed that the proposed ensemble achieves around 78% accuracy on two datasets and more than 99% accuracy on one dataset, which is better compared to base classifiers and two popular ensembles.

The Possibility of Using Oil Pomace as a Substitute for Walnuts (Juglans regia L.) in Muesli Bar Technology

The utilization of food industry waste to create innovative, high-quality products with reduced environmental impact is a growing trend in food technology. Walnut oil pomace, a byproduct of walnut oil production, is rich in nutrients and bioactive compounds, making it an excellent candidate for reuse in muesli bars as a replacement for walnuts. The aim of the study was to evaluate the possibility of replacing walnuts with oil pomace in muesli bar recipes and to assess whether the resulting product meets quality standards. Ground expeller walnut oil pomaces and aqueous extract were tested, with a bar containing ground walnuts serving as the reference sample. The bars were evaluated for sensory, physicochemical, and antioxidant properties, and their nutritional values were assessed. Results showed that the pomace-enriched bars exhibited satisfactory physicochemical properties, with texture, color, and safety (as measured by water activity and pH) comparable to the control bars. Sensory evaluations classified all bars as acceptable, with no significant differences in nutritional value. The study concludes that walnut pomace holds promise as a sustainable ingredient in food technology, potentially expanding product diversity while reducing environmental impact. This concept aligns with promoting sustainable practices in food manufacturing.

Planting System and Cultivar Influence Olive Key-Pests Infestation in an Olive-Growing Vocated Area

Traditional and intensive planting systems have paved the way for the phenomenon of intensification, with the super high-density (SHD) system being the most prominent. This system has demonstrated high levels of profitability due to both the reduction in production costs achieved through complete mechanization and a significant increase in olive oil production per hectare, stemming from the more efficient utilization of resources such as light, water, and nutrients. The aim of this study was to evaluate, in a vocated olive-growing area, the phytosanitary status of a SHD olive orchard compared to a traditional one (TRD). The research focused on six key olive pests, considering the interaction between planting systems and eight cultivars in a semi-arid environment. The comparative analysis of pest infestations across the two planting systems revealed significant and complex patterns in pest population distribution and intensity. Overall, the planting system appeared to be the main factor influencing pest dynamics. The SHD olive orchard exhibited the highest infestation levels of Otiorhynchus cribricollis, Palpita unionalis, and Bactrocera oleae. Conversely, in the TRD system, the highest infestation levels of Saissetia oleae, Euphyllura olivina, and Prays oleae were observed. Moreover, the study highlighted a less pronounced effect of cultivars on the prevalence of all monitored key pests. These findings underscore the potential for developing more sustainable and effective pest management strategies tailored to specific planting systems. Furthermore, the results contribute to advancing eco-friendly control approaches and improving pest infestation management practices. Additional research will be necessary to deepen the understanding of these key pests and their interactions within different olive-growing systems.

Potential use of pumpkin seed oil production waste as a functional ingredient in pasta: some chemical, physical, textural, microstructural and sensory properties and a TOPSIS application

Potential use of pumpkin seed oil production waste as a functional ingredient in pasta: some chemical, physical, textural, microstructural and sensory properties and a TOPSIS application

Study on polymer-containing oily sludge as a potential fuel by combustion thermochemistry

The environmental and resource issues posed by oil sludge have sparked a renewed interest in cleaner and more efficient oil production. The investigation on the combustion process of polymer-containing oily sludge (POS) is expected to open up new markets for POS as an alternative fuel. TGA was used to examine the combustion behaviour, kinetics, and thermodynamics of POS, and X-ray fluorescence (XRF) was used to measure the chemical composition of POS ash to predict ash fouling and slagging. Based on the TG-DTG curves, the mass loss of POS in combustion studies was split into four major areas. The combined calculation method of model-free methods, Flynn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS), was applied to determine the activation energies from stage 1 to stage 4, which were 47.89 kJ/mol, 66.09 kJ/mol, 190.55 kJ/mol, and 98.37 kJ/mol, respectively. A four-stage kinetic model (D4→D2→D3→R2) was established to describe the combustion process of POS. Compared to other conventional sludges, POS has a relatively low activation energy and is more susceptible to thermochemical transformations. The difference between the enthalpy change (ΔH) and activation energy (E) indicated that the reactions benefit the formation of the activated complex. Meanwhile, the change in entropy (ΔS) implied the thermodynamic disequilibrium in the 3rd stage of POS and completion of the thermal conversion at the end of the reaction. The change in Gibbs free energy (ΔG) increased in a stepwise manner and its lower average value reflected the greater reaction favourability of combustion for POS. The composition of POS ash was mainly metal oxides, with the slagging index, fouling index, and slagging viscosity index of 1.0, 9.1, and 32.0, respectively. POS ash has high fouling and slagging, with special attention in the combustion application.

Effects of Fines Migration and Reservoir Heterogeneity on Well Productivity: Analytical Model and Field Cases

Abstract Formation damage due to fines migration after water breakthrough during oil and gas production results in significant well productivity decline. A recent study derived an analytical model for fines migration during commingled water–oil production in homogeneous reservoirs. Yet, reservoir heterogeneity highly affects formation damage and well productivity. This article develops an analytical model for layer-cake reservoirs. We develop a novel methodology for characterizing productivity decline by considering the impedance as a function of water-cut, two quantities that are commonly measured throughout the production life of the well. The methodology is based on a new analytical model for inflow performance in layer-cake reservoirs under fines migration. The new model integrates pseudo-phase-permeability functions for commingled water–oil production with equations for fines release and induced permeability damage. The analytical model reveals linear well impedance growth versus water-cut increase, where the slope is determined by a modified form of the mobility ratio which includes the extent of formation damage. This linear form is shown to arise when the formation damage factor is constant, regardless of the distribution of reservoir permeabilities. The model is validated by comparison with production histories of five wells from three fields, which exhibit good agreement with the linear trend predicted by the new model. The explicit formulae allows for the prediction of productivity at abandonment, determining the optimal well stimulation time, as well as reconstructing skin values during the early stages of production to better estimate the influences of other formation damage factors, like those induced during drilling and completion.

Integrated model for digital oil field development management

Providing the extractive industry with new technologies to maintain the levels of oil and gas production planned in the strategy of the Russian Federation is the most important task. First of all, an increase in profitable reserves must be ensured; this goal can be achieved both through geological exploration and through the capabilities of “digital transformation” and the formatting of decision-making systems. A field controlled by artificial intelligence is a new reality. At the same time, the main task of AI is not to reduce jobs or completely replace humans in the field, but to provide a systematic, objective approach to decision-making based on physics and mathematics, and not on the personal experience of an individual. Currently, the main planning tool in the oil and gas industry is a geological and hydrodynamic model. Recently, thanks to an increase in design capacity, the industry has made an evolutionary leap in this direction and is transitioning to integrated modeling that combines both the underground and surface parts of the field. The future is neural network technologies, combined with classical methods into a single digital environment for optimizing all processes, from reservoir to processing and sales of products. In the new paradigm, the process of development management at different stages of field development requires a radical transformation of both the tools used for this and changes in governing documents. To meet the ever-accelerating pace of progress, timely updating of the legislative framework is required, development of regulations for integrated modeling, including all elements of research and production, from seismic exploration to field development; in addition, each stage of field development requires its own requirements for the quality and volume of initial information, in accordance with the new production paradigm.