Oil Reserves Research Articles

Taking Alberta Back: Faith, Fuel, and Freedom on the Canadian Far Right

Alberta, Canada is both a major extractive zone—home to the world’s third largest proven oil reserves, mostly in the form of oil sands located in the north of the province—and a place whose political culture has been profoundly influenced by evangelical Christianity. It is both “petro province” and “God’s province”. Despite these distinct political economic and socio-cultural features, relatively little scholarly attention has been given to the contemporary relationships among them. To explore this, we profile the populist far-right social movement organization Take Back Alberta (TBA), which, by channeling the interlocking “freedom” and separatist movements into the governing United Conservative Party (UCP), played a pivotal role in Alberta Premier Danielle Smith’s rise to power. We ask the following question: what role do religion and a populist defense of the fossil fuel industry (or “extractive populism”) play, both ideologically and organizationally, within TBA? Drawing from TBA-related documents, including websites, podcasts, social media, and speeches, our analysis produces two key findings: first, that TBA deploys a radical, far-right version of extractive populism, which “anchors” the Danielle Smith government, and, second, that evangelical Christianity contributes to this extractive populism organizationally—by impacting TBA’s membership and resource infrastructure—and discursively, by influencing the collective action frames utilized by TBA leaders in advocating for the interests of the fossil fuel industry.

Three‐dimensional static reservoir modelling of Kareem sandstone reservoir, Tawilla Oil Field, at the southern region of Gulf of Suez, Egypt

The Gulf of Suez, which contains Egypt's oldest oil fields, is one of North Africa's most well‐known oil regions. There are more than 80 conventional oil fields in Egypt's Gulf of Suez, some of which have reservoirs that stretch back to the Precambrian and Quaternary. In close proximity to the southern entrance of the Gulf of Suez is the Tawilla West oilfield. The oil field Tawilla West is believed to consist of rotating fault blocks that descend in a south‐west direction. The main producing reservoirs are the Miocene section reservoirs, the Belayim and Kareem sandstones. The current research is focusing on the structural elements affecting this giant field to update the field structural model using the newly processed 3D seismic survey, the acquired data from newly drilled wells and the associated different logging techniques. The seismic information quality varied from poor to fair. The quality of the interpreted stratigraphic horizons and geological faults was mainly controlled by the seismic information quality. The research used seismic attribute analyses to improve interpretation and incorporate additional features, enabling better hydrocarbon potential identification and characterization of the reservoirs. Several geological structure contour maps and cross‐sections were generated to help in delineating and understanding the reservoir's extension. Based on the detailed correlation study, we were able to detect the faults that affected the structure of the Tawilla West field in detail, define their throw amounts and directions, and identify the missed sections across the studied area. This study introduces an updated model scenario to show the differences and their effect on the field development plan and recommendations. By examining subsurface geologic structural characteristics and evaluating petrophysical data, a 3D static reservoir model was created to resolve structural settings and hydrocarbon trapping, providing detailed information on the field and identifying new opportunities for future development. The research discovered that the updated detailed 3D structural model may support the Kareem Reservoir development plans and encourage drilling, workover and dynamic operations to assign development possibilities in the correct area. According to the established model, there are at least three options in the study's attic areas that might boost oil output and oil reserves for the field while avoiding further failures.

Pollution-adjusted optimal leasing value of oil and gas reserves

Pollution-adjusted optimal leasing value of oil and gas reserves

Bioremediation petroleum wastewater and oil-polluted soils by the non-toxigenic indigenous fungi.

Soil and wastewater samples contaminated by petroleum-related industries were collected from various locations in Saudi Arabia, a country known for its vast oil reserves. The samples were analyzed for their physicochemical properties, including the presence of metals, petroleum hydrocarbons, and aromatic compounds. A total of 264 fungal isolates were analyzed and categorized into eight groups of Aspergillus (194 isolates) and four groups of Penicillium (70 isolates). The potential of these fungal groups to grow in oil or its derivatives was investigated. Two isolates, Aspergillus tubingensis FA-KSU5 and A. niger FU-KSU69, were utilized in two remediation experiments-one targeting wastewater and the other focusing on polluted soil. The FA-KSU5 strain demonstrated complete removal of Fe3+, As3+, Cr6+, Zn2+, Mn2+, Cu2+ and Cd2+, with bioremediation efficiency for petroleum hydrocarbons in the wastewater from these sites ranging between 90.80 and 98.58%. Additionally, the FU-KSU69 strain achieved up to 100% reduction of Co2+, Ba2+, B3+, V+, Ni2+, Pb2+ and Hg2+, with removal efficiency ranging from 93.17 to 96.02% for aromatic hydrocarbons after 180min of wastewater treatment. After 21days of soil incubation with Aspergillus tubingensis FA-KSU5, there was a 93.15% to 98.48% reduction in total petroleum hydrocarbons (TPHs) and an 88.11% to 97.31% decrease in polycyclic aromatic hydrocarbons (PAHs). This strain exhibited the highest removal rates for Cd2+ and As3+ followed by Fe3+, Zn2+, Cr6+, Se4+ and Cu2+. Aspergillus niger FU-KSU69 achieved a 90.37% to 94.90% reduction in TPHs and a 95.13% to 98.15% decrease in PAHs, with significant removal of Ni2+, Pb2+ and Hg2+, followed by Co2+, V+, Ba2+ and B3+. The enzymatic activity in the treated soils increased by 1.54- to 3.57-fold compared to the polluted soil. Although the mixture of wastewater and polluted soil exhibited high cytotoxicity against normal human cell lines, following mycoremediation, all treated soils and effluents with the dead fungal biomass showed no toxicity against normal human cell lines at concentrations up to 500 µL/mL, with IC50 values ≥ 1000 µL/mL. SEM and IR analysis revealed morphological and biochemical alterations in the biomass of A. tubingensis FA-KSU5 and A. niger FA-KSU69 when exposed to petroleum effluents. This study successfully introduces non-toxigenic and environmentally friendly fungal strains play a crucial role in the bioremediation of contaminated environments. Both strains serve as low-cost and effective adsorbents for bio-remediating petroleum wastewater and oil-contaminated soil. Heavy metals and hydrocarbons, the primary pollutants, were either completely removed or reduced to permissible levels according to international guidelines using the dead biomass of FA-KSU5 and FA-KSU69 fungi. Consequently, the environments associated with this globally significant industry are rendered biologically safe, particularly for humans, as evidenced by the absence of cytotoxicity in samples treated with A. tubingensis FA-KSU5 and A. niger FA-KSU69 on various human cell types.

Improving fluid identification in well logging using Continuous Wavelet Transform and Vision Transformers: An innovative approach

Well logging fluid prediction is one of the key steps in assessing oil and gas reserves. By analyzing downhole logging data, different types of fluids contained in underground rocks, such as crude oil, natural gas, and water, can be determined. This information is crucial for assessing the abundance and recoverable reserves of oil and gas resources and helps guide oil and gas exploration and development work. We have introduced a novel model called CWT (Continuous Wavelet Transform)-ViT (Vision Transformer). CWT can simultaneously provide frequency information at different scales, enabling the model to analyze downhole logging data more comprehensively and accurately at different scales. Underground rock structures often exhibit features at multiple scales, and CWT can effectively capture these features, aiding in better differentiation of different types of fluids. The ViT model utilizes the Transformer architecture, allowing for global attention over input sequences without being limited by sequence length. This enables the model to comprehensively understand the overall information of downhole logging data and extract richer features. For complex geological structures and fluid distributions in geological exploration, the global attention mechanism helps the model better grasp the overall situation, thereby improving the accuracy of fluid prediction. When we used the CWT-ViT method for well logging fluid prediction, we achieved a high accuracy rate of 97.50% in the first dataset, which further improved to 97.77% in the second dataset. These results demonstrate the significant robustness and efficiency of the CWT-ViT method in lithology prediction using well logging data. We also conducted blind well experiments, and our CWT-ViT model outperformed other models, achieving a blind well prediction accuracy of 97.36%. Therefore, the experiments indicate that the key to improving accuracy in well logging fluid prediction with CWT lies in its multiscale analysis capability, effectively capturing different fluid characteristic frequencies. Additionally, CWT enhances signal features and removes noise, increasing the precision of fluid identification. Finally, the integration with ViT further optimizes fluid prediction performance, making it outstanding in complex geological environments. The advantages of ViT in fluid prediction include its excellent sequence modeling capability, effective handling of long-distance dependencies, and enhanced ability to capture fluid characteristics in complex well logging data.

Research Progress onLeak Prevention and Plugging Technology in Deepwater Drilling

Abstract With the continuous development of global oil and gas resources, onshore and shallow water crude oil production is no longer sufficient to meet the demand. Therefore, deepwater oil and gas exploration and development have attracted high attention from various countries. China’s oceans are vast and rich in offshore oil resources, especially in the South China Sea, where oil and natural gas reserves are enormous. In recent years, it has become a key focus of national offshore oil exploration and development. The increasing complexity of deep-sea well leakage in the ocean and the increasing difficulty of management have brought great challenges to drilling construction and also caused significant economic losses. Therefore, the research on leak prevention and plugging technology for deep water in the ocean has become particularly important. This article investigates the current research status of deep water leakage prevention and plugging technology both domestically and internationally, discusses the main problems that exist in the development and drilling process of deep water oil and gas fields, analyzes the reasons for well leakage, and proposes corresponding solutions.

A Deep Learning Structure Correction Method Under the Influence of Special Lithology Body

Abstract In the process of precise exploration and development of oil and gas reservoirs, the accurate implementation of the target layer structure plays a vital role in the increase of oil reserves and the success of drilling. However, with the gradual deepening of the research, it is found that in the overlying strata of oil and gas reservoirs, special lithological bodies with strong heterogeneity and abnormal velocity are usually locally developed, which directly affects the construction of seismic data migration velocity, resulting in structural distortion at the local position of the reservoir in the process of data interpretation. Focusing on the structural change caused by the abnormal velocity, the deep learning algorithm is used to accurately predict the velocity of the special lithologic body and realize the accurate correction of the structure. Firstly, based on the combination of seismic and geological understanding, the geological model of the target layer and the overlying special lithologic body is constructed, and the distribution law of the special lithologic body is identified by the forward simulation method. Then use the well-side seismic trace and P-wave velocity curve to train the velocity data through the deep learning method and apply the training results to the post-stack seismic data to obtain the accurate P-wave velocity body. Finally, the real formation velocity over the target layer is restored to achieve reservoir structure correction. Based on this method, the research experiment was carried out in the M block of the Tarim Basin, and the spatial distribution range of the special lithology body was carved. The data error between the migration velocity body and the abnormal high-velocity body was calculated, and the target layer structure in the study area was corrected.

State ownership and financial reporting quality: Evidence from natural advantage industries

Using a hand-collected sample of state-owned enterprises and newly privatized firms around the globe, we examine financial reporting quality in natural advantage (substantial oil reserves or mineral deposits) industries. We find that ultimate state ownership tends to deteriorate financial reporting quality. Such a finding tends to occur particularly in countries with low shareholder minority protection, low financial development, high resource extraction intensity, low freedom of the press, collectivist societies, poor government anti-diversion policies, and in resource-dependent countries. Finally, we document that ultimate state ownership in the context of better financial reporting quality is associated with exacerbated capital expenditures, which indicate resource overextraction. Such a finding applies particularly to resource-dependent countries and civil-law countries.

Prospects for increasing oil resources and reserves in the Yenisei-Khatanga regional trough

The capabilities of discovering large oil fields in the central part of the Yenisei-Khatanga regional trough were considered. Processing and integrated interpretation of geological, geophysical and geochemical information provided the basis for the identification of four promising oil accumulation zones (an area of 58 thousand km2). For the multi-deposit Payakha oil field, three more zones located at depths of 3.2– 3.5 km were identified at the base of the clinoform complex. This made it possible to ensure the increment of localized recoverable oil resources of D1l category.

Calculation Modeling of Adsorbed and Bulk-Phase Oil Resources Based on Molecular Dynamics Simulations

Summary Nanopores prevalent in shale reservoirs significantly impact shale oil occurrence characteristics due to the strong intermolecular forces between crude oil molecules and the pore walls. Unlike bulk-phase oil, which is more readily recoverable with current technologies, the behavior of oil within these small-scale environments presents unique challenges. This study utilizes molecular dynamics simulations (MDSs) to investigate the characteristics of shale oil in slit nanopores, with the goal of refining a model that estimates the quantities of both bulk and adsorbed oil in shale reservoirs. We constructed models for three types of nanopores—organic graphene, illite, and quartz—using n-hexane (n-C6H14) as a proxy for shale oil. Our analysis reveals that mineral composition significantly influences fluid adsorption capacity, ranked as graphene > illite > quartz. Unlike prior research, we found that the critical flow pore diameter, which dictates the transition from adsorbed to free-flowing oil, cannot be simplistically equated to the combined thickness of adsorption layers. Specifically, in graphene pores with a diameter of 3.8 nm, the fluid mass density at the pore center still exhibits adsorption layer characteristics, forming up to nine layers. Building on these insights, we revised the shale reservoir resource estimation model to account for adsorption variances across different pore types. Our findings highlight the significant role of adsorbed oil in nanopores within shale reservoirs. Data from the Gulong shale oil block in the Daqing oil field indicate that adsorbed oil constitutes 37.15% of geological reserves, while bulk-phase oil accounts for the remaining 62.85%. This research provides essential data for accurately calculating shale oil reserves in nanopores, which are crucial for the effective exploitation of shale oil reservoirs.

The Correlation Dynamics Between Sensex 30 Returns and INR/USD Exchange Rate Movements

The Sensex 30 is a benchmark index for India's largest companies, indicating the health of the stock market. Its movements are influenced by domestic economic conditions, corporate performance, and global trends. The INR/USD exchange rate, which represents the Indian rupee vs. the US dollar, is crucial for India's international trade and investment. A depreciating rupee benefits export-oriented companies but increases import costs, affecting market performance. Understanding this dynamic is essential for investors and policymakers. The fluctuating link between the INR/USD currency pair and SENSEX 30 stock index is examined in this study from 2014 to 2024, with an emphasis on how changes in the exchange rate affect stock market performance. As India continues to integrate into the global economy, the interaction between foreign investments and the Indian stock market has become increasingly relevant for understanding investor sentiment and economic stability. This study particularly examines how returns from the SENSEX 30, an index that monitors 30 of India's biggest and most traded firms, are impacted by changes in the INR/USD exchange rate. The research's main finding is that there is a strong positive correlation between the INR/USD exchange rate and the SENSEX 30 index, with a rise of 1 in the SENSEX 30 for every 0.90 increase in the exchange rate. This implies that the depreciation of the Indian currency (INR) in relation to the US Dollar (USD) may result in increased stock market returns, especially in industries that rely heavily on exports, as Indian goods become more competitive in international markets due to the weaker currency. On the other hand, persistent depreciation may also result in higher import prices and inflationary pressures, which might be detrimental to business profitability and the state of the economy as a whole. Given that currency changes may have an impact on their investment decisions, foreign institutional investors (FIIs) are essential to this dynamic.. Decreased international gains are eroded by a lower INR, which frequently leads to portfolio modifications and more market volatility. Exchange rate fluctuations and stock market performance are influenced by the participation of foreign institutional investors (FIIs) and the Reserve Bank of India's (RBI) monetary policy choices. For example, the RBI's changes to interest rates have an effect on investor mood and influence market movements. Global economic variables that affect the US stock market and exchange rate include geopolitical tensions, changes in the price of commodities, particularly oil, and US Federal Reserve policies. The study uses a variety of statistical techniques, including as trend analysis, a t-test, and correlation analysis, to assess the link between the performance of the SENSEX 30 and the INR/USD exchange rate during a ten-year period. The results of the t-test demonstrate that the difference between the mean values of the SENSEX 30 and the INR/USD exchange rate is statistically significant, with a t-statistic of 30.278 and very tiny p-values. The SENSEX 30 exhibits a significantly bigger variation than the INR/USD, suggesting that the stock market is more volatile than the currency rate. This result is in line with predictions because stock markets are often more erratic than exchange rates. As a result, the study emphasizes how much exchange rate fluctuations affect the Indian stock market. It is recommended that investors keep a careful eye on currency changes since they have the International Journal of Scientific Research in Engineering and Management (IJSREM) Volume: 08 Issue: 09 | Sept - 2024 SJIF Rating: 8.448 ISSN: 2582-3930 © 2024, IJSREM | www.ijsrem.com DOI: 10.55041/IJSREM37610 | Page 2 potential to impact business profitability and stock market performance, particularly in industries that depend on imports or exports. The results also emphasize how crucial it is to diversify portfolios and hedge against risk related to currencies in order to successfully manage the intricate relationships between monetary policy, market volatility, and global economic situations.

Efficiency analysis of the application of thermal methods at the Pirallahi and Darwin bank fields

The efficiency of oil and gas field development is associated with the correct choice of appropriate measures to be implemented. This research considers the Pirallahi and Darwin Bank fields with hard-to-recover oil reserves. The Pirallahi field is located in the eastern part of the Absheron Peninsula. The initial balance reserve for the facility is 4 million tons, and the level of reserve utilization is 19%. Among the notable features, the Pirallahi deposit represents the southern fold of the PK (Pre-Kirma- ki) horizon. Across the horizon, the initial balance reserve is approximately one million tons, and the utilization rate is 17%. In other groups, the level of utilization exceeds 20%. Accordingly, the volume of initial balance reserves ranges between 8-35 million tons. Industrially important objects here are KSv (Kirmaki suite, fifth horizon), KSn (Kirmaki suite, n horizon), and PKS (Post-Kirmaki suite). To develop oil reserves, more than 1000 production wells were drilled at different stages of the development process. The southern fold consists of a brachyanticline extending from northwest to southeast. The main tectonic element of the southern fold is its thrust nature and its very complex tectonic structure. The fold is heavily watered. Therefore, to increase the efficiency of developing these fields, it is necessary to use appropriate methods of influencing the formations. To enhance the efficiency of the development process in the northern part, the in-situ combustion method was applied. The Darwin Bank field belongs to the Absheron archipelago and has a tectonic brachyanticlinal structure. The structure is complicated by numerous longitudinal and transverse faults. It is divided into six tectonic zones by several transverse and one longitudinal fault passing through the crest. Darwin Bank oils are heavy oils with low sulfur content. In addition, low paraffin and high resin content are observed in the composition of field oil. For both fields, the recovery rate of geological reserves fluctuates around 30%. The article, primarily, examines the selection of objects and the use of enhanced oil recovery methods in these fields. The in-situ combustion method was used in the northern part of the Pirallahi field and Darwin Bank.

Estimation of reservoir properties using pre-stack seismic inversion and neural network in mature oil field, Upper Assam basin, India

The mature oil fields require comprehensive characterization for enhanced hydrocarbon production, and subsequently demands estimation of reservoir properties. The key properties viz. volume of clay, effective-porosity, hydrocarbon-saturation has been evaluated for an aging Oligocene reservoir of Upper Assam basin, located in northeastern India from seismic and well log data. Elastic properties (acoustic and shear impedance) and density are derived from pre-stack inversion of 3D seismic data. These elastic properties are analyzed for their sensitivity for discrimination of lithology and fluid-content, and many derived attributes are computed from elastic properties. These attributes are assessed for their predictability to predict the target reservoir properties using multi-attribute analysis. For each of the target property neural network is trained with the most predictable attributes, and multi-dimensional, non-linear neural network models are created using multilayered feed forward neural network (MLFN), followed by Probabilistic neural network (PNN). The specific neural network models for each target property are employed for quantitative estimate of volume of clay, effective-porosity, hydrocarbon-saturation in inter-well regions. The estimated properties leverage the identification of untapped oil reserves and provide promising opportunity for enhanced production through drilling of infill wells.

Accurate identification of salt domes using deep learning techniques: Transformers, generative artificial intelligence and liquid state machines

AbstractAcross various global regions abundant in oil and natural gas reserves, the presence of substantial sub‐surface salt deposits holds significant relevance. Accurate identification of salt domes becomes crucial for enterprises engaged in oil and gas exploration. Our research introduces a precise method for the automatic detection of salt domes, leveraging advanced deep learning architectures such as U‐net, transformers, artificial intelligence generative models and liquid state machines. In comparison with state‐of‐the‐art techniques, our model demonstrates superior performance, achieving a stable and validated intersection over the union metric, indicating high accuracy and robustness. Furthermore, the Dice similarity coefficient attaining underscores the model's proficiency in closely aligning with ground truth across diverse scenarios. This evaluation, conducted on 1000 seismic images, reveals that our proposed architecture is not only comparable but often surpasses existing segmentation models in effectiveness and reliability.

Investment Analysis for Monetization of Marginal Oil Reserves: An Alpha Field Joint Operation Case Study

Challenges and opportunities are faced in the development of marginal oil reserves that are often uneconomical to exploit conventionally. The main objective of this study was to determine whether the project is a viable investment based on the given assumptions, as well as whether the potential returns can justify the risks associated with marginal oil reserves. The research method involved the use of key financial metrics such as Net Present Value, Internal Rate of Return, and Payback Period, using a discount rate of 10%, which is standard in the oil and gas industry. The results show that the project has a positive NPV of USD 124,462.38, an IRR of 13.13%, and a PBP of 4 years and 5 months. These results indicate that the project is financially viable, with returns exceeding the capital cost of the project. Further sensitivity analysis identified that oil prices and production levels are the most critical factors affecting the financial outcome of the project. Compared to the WACC of 10.25%, the IRR of 13.13% indicates that the project exceeds the minimum required rate of return, thus justifying the investment. The implications of this study highlight the importance of proper operational management and market risk mitigation to maintain profitability.

RESEARCH OF THE COMBUSTION PARAMETERS OF GASOLINE WITH ADDITIONAL HYDROGEN IN A SPARK-IGNITION ENGINE IN EXTERNAL SPEED CHARACTERISTIC MODES

The directions of development and improvement of road transport around the world are inextricably linked to the desire to reduce the use of cars “on traditional fuels” due to limited oil and environmental safety of mankind. Since the modes of external speed characteristic are the most typical for the operation of cars in cities, the study of environmental performance of engines in these modes is an urgent task. Therefore, finding ways to reduce carbon dioxide emissions from automobile engines at high-speed modes is an urgent task. The rapid growth in the number of cars with internal combustion engines and the inevitable decline in world oil reserves necessitate the development and implementation of energy-saving technologies and the use of alternative fuels. Research aimed at finding ways to improve the fuel efficiency and environmental performance of automotive engines is relevant. One of the promising areas is the influence on the combustion process in gasoline engines by using additives of alternative fuels, which include hydrogen. The presented study of the parameters of combustion of gasoline with hydrogen additive in a spark ignition engine at external speed characteristics is a comprehensive analysis of the combustion process of a gasoline-hydrogen mixture and determination of its effect on the concentration of carbon dioxide in exhaust gases by developing a mathematical model that takes into account the composition of the mixture components and features of the combustion process, allows for sufficiently accurate calculation of the operating process of an engine with hydrogen additive at ψ ≤ 10%, its identification by the results of experiments. In the course of the study, dependencies were developed to determine the combustion parameters of the Wiebe model, taking into account the addition of hydrogen to gasoline in the modes of external speed characteristics, and the effect of hydrogen addition on the concentration of CO2 in exhaust gases was analyzed. It is shown that with an increase in the hydrogen additive to 10% by mass fraction to gasoline, there is a decrease in CO2 emissions to almost 30% in the external speed characteristic modes, which corresponds to modern environmental standards for gasoline internal combustion engines.

When do petrostates diversify their exports? Urgency, interests, and policy design in Egypt, Kazakhstan, and Malaysia

AbstractMotivationThe need to diversify their economies is an enduring challenge for fossil fuel‐dependent countries, one which will become ever more important as the world seeks to decarbonize. But the conditions under which major oil‐producing countries (petrostates) seek to diversify their exports—and those under which their attempts succeed—are poorly understood.PurposeThis article tests competing explanations for the successes and failures of petrostates' export diversification.Methods and approachWe employ a comparative case study approach using qualitative evidence from two comparatively successful diversification cases—Egypt and Malaysia—and one less successful case—Kazakhstan—selected using a Theil index of export concentration.FindingsThe evidence indicates that Egypt and Malaysia's more successful outcomes stemmed more from necessity and policy design than from differences in domestic institutions and interests. All three countries were motivated to diversify by price volatility and declining revenues at various points from the 1980s to the 2000s and beyond, but reserve depletion was a greater threat in Egypt and Malaysia. As such, they adopted a more balanced approached to diversification, one that combined liberalization with state intervention.Policy implicationsThese cases suggest that petrostates may be willing and able to diversify as the global shift toward renewables raises the prospect of unburnable oil reserves. Petrostates can diversify efficiently by using a basket of policies that includes a mix of economic liberalization and government intervention to create investment and incentives in non‐oil tradeable sectors and nurture infant industries. Opposition to reforms in petrostates can be addressed by selectively compensating vested interests.

STUDY OF TEMPERATURE FIELDS NEAR A WELL DURING FILTRATION OF VISCOPLASTIC OIL

The work examines the time variation of fluid temperature during non-isothermal filtration of viscoplastic oil near a well. It is known that a characteristic feature of modern oil production is an increase in the share of hard-to-recover oil reserves, which include viscoplastic oils. According to their rheological characteristics, such oils are non-Newtonian liquids and, therefore, their filtration process is not described by Darcy’s linear law. When filtering fluids that are not described by Darcy's law, it is necessary to use nonlinear filtration laws, which make it possible to more adequately describe the processes occurring in productive formations when hydrocarbons are displaced from them. To describe the nonlinear filtration law, empirical formulas obtained by approximating data from laboratory experiments are usually used.In the works of V.V. Devlikamov and his co-authors provide experimental data on the dependence of viscosity on shear stress for high-viscosity oils. They have been shown to be approximated quite well by a sigmoid function. However, the problem then becomes significantly nonlinear. Subsequently, in order to simplify finding a solution to the problem of filtration of high-viscosity oil, experimental data were obtained by V.V. Devlikamov and his co-authors were approximated by broken lines.In this work, the experimental data are approximated by a sigmoid function, which allows for more accurate calculations. Assuming that the viscosity and density of oil do not depend on temperature, which is typical for natural development modes, the results of calculations of temperature changes over time near the well are presented. It is shown that the temperature of viscoplastic oil in the first hours after starting a well differs significantly from the temperature of Newtonian oil (oil with constant viscosity). Thus, if the temperature of Newtonian oil continuously increases, then the temperature of viscoplastic oil immediately after starting a well increases and coincides with the temperature of oil with constant viscosity, then drops and after some time begins to increase again. The work shows that such an unusual change in the temperature of viscoplastic oil over time is associated with a change in the zone of destruction of the formation structure.

APPROACH TO CREATION OF GEOLOGICAL AND RESERVOIR SIMULATION MODEL AND METHODS FOR HISTORY MATCHING OF RESERVOIR ENERGY STATE

Under conditions of complex geological structure and substantial share of hard-to-recover oil reserves, reservoir simulation is a key tool in reservoir management. Direct problems solved by reservoir simulation include forecasting of the production performance, control and management of reservoir development, and localization of residual oil reserves. Inverse problem solution is useful for updating the knowledge of geological structure, reservoir quality, and historical production data by means of history matching. The quality of history matching is fundamental to ensure reliable future forecasts and localization of residual oil zones. The main approaches to appropriate history matching rely on analysis and adjustment of well logging and geological parameters, as well as checking and correction of errors, inadequate historical data, application of physics-based and reasonable approaches and tools. The prerequisite for adequate history matching and predictive ability of the resultant reservoir simulation model is the compliance of simulated and actual energy state of the reservoir. In this paper, the initial stage of reservoir simulation is performed, the approach to history matching of reservoir energy state aimed at improving the quality of further predictions is described as exemplified by one of the production areas of Russian oil field. The main causes of poor history match of formation and bottomhole pressures are revealed. These causes are grouped as follows: — geological causes/reservoir quality, which include permeability field distribution, reservoir connectivity, and determination of rock and fluid compressibility;— technical causes (during reservoir simulation), that is model limitations in case of larger areas, the need to use sector models, consideration of buffer region;— technological causes, including inadequate historical data or lack of data, detection of behind-the-casing flows and production casing leaks in wellbore, etc. For each group of factors that have a substantial impact on reservoir pressure, recommendations and methods of energy state history matching on geological and reservoir simulation models are provided, examples are given.

ASSESSMENT OF THE IMPACT OF WELL GRID DENSITY ON OIL RECOVERY UNDER CONDITIONS OF UNCERTAINTY

The density of the well grid is one of the most important parameters that has a significant impact on the rate and amount of oil reserves extraction. As practice shows, existing approaches to the reliable assessment and identification of the degree of influence of this indicator on oil recovery do not allow us to adequately form an idea of the dynamics of reservoir processes and their role in making managerial decisions in conditions of uncertainty. Taking into account the decrease in the number of hydrodynamic and geophysical studies conducted in relation to the total number of wells in operation at fields that are being developed for a long time or just being put into development, the issue of predicting the oil recovery coefficient according to the list of geological and field parameters remains open and requires an urgent solution, including those related to the use of unique complex algorithms. The purpose of the work is to determine the relationship between the density of the well grid and the final coefficient of oil recovery in the development of fields in natural conditions using computer modeling systems. The research methodology consists of the use of existing scientific and methodological approaches to the processing of geological and commercial information in conditions of different densities in combination with the use of various advanced systems for identifying hidden patterns. Geological and statistical models have been defined for the oil deposits of the Famensk tier of the South Tatar arch of the Volga-Ural oil and gas province, allowing for the forecasting procedure for groups of objects identified during differentiation, subject to the dynamic density of geological and field information and various technical and economic indicators of field development. A comprehensive interpretation of the nature and degree of influence of geological and technological parameters on the amount of oil reserves production has been carried out. The need for preliminary differentiation of deposits based on identification with the subsequent use of the presented geological and statistical models to reduce the risks of making erroneous decisions during activities aimed at optimizing the development of analog facilities and rational extraction of residual oil reserves is reliably substantiated.