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Copyright of Petroleum Geology & Oilfield Development in Daqing is the property of Editorial Department of Petroleum Geology & Oilfield Development in Daqing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

CO2 pre-fracturing is an innovative technique for enhancing oil and gas production in unconventional reservoirs. Despite its potential, the mechanisms of CO2 pre-fracturing influencing fracture propagation, particularly in ultra-deep reservoirs, remain inadequately understood. This study investigates the CO2 pre-fracturing process in ultra-deep sandstone reservoirs of the central Junggar Basin. A 3D geomechanical model was established using RFPA3D-HF based on rock mechanical parameters from laboratory experiments. The study examines the effect of in situ horizontal stress differences, CO2 pre-injection volume, and slickwater injection rate on fracture complexity index (FCI) and stimulated reservoir volume (SRV). The results reveal that in situ horizontal stress differences are the primary factor influencing fracture propagation. In ultra-deep reservoirs, high horizontal stress difference hinders fracture deflection and bifurcation during slickwater fracturing. CO2 pre-fracturing, through the pre-injection of CO2, reduces formation breakdown pressure and increases reservoir pore pressure due to its low viscosity and high permeability, effectively mitigating the effect of high horizontal stress differences and significantly enhancing fracturing effectiveness. Furthermore, appropriately increasing the CO2 pre-injection volume and slickwater injection rate can increase fracture complexity, resulting in a larger SRV. Notably, adjusting the CO2 pre-injection volume is more effective than adjusting slickwater injection rate in enhancing oil production. This study provides scientific evidence for selecting construction parameters and optimizing oil recovery through CO2 pre-fracturing technology in deep unconventional oil reservoirs and offers new insights into CO2 utilization and storage. [ABSTRACT FROM AUTHOR]

ABSTRACT The COVID‐19 pandemic has significantly impacted global economies, disrupting various sectors, including energy production. This study examines the effects of COVID‐19 on oil and natural gas production in 14 producer countries between January 2020 and December 2021. Using the generalised method of moments (GMM) and panel data analysis, we explore the relationship between pandemic‐related disruptions, energy prices and trade openness on the production of non‐renewable energy sources. Results indicate that COVID‐19 negatively influenced both oil and gas production, with a stronger impact observed on oil. While trade openness positively contributed to energy production, rising energy prices exacerbated the decline in output. The findings underscore the importance of resilience strategies, including robust energy policies and adaptive measures, to mitigate the effects of future global crises. This research contributes to the literature by providing comprehensive insights into the production challenges and opportunities within the energy sector during a pandemic. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of oil production on economic development and poverty alleviation from 1990 to 2022. As one of Africa's largest oil producers, Nigeria has witnessed significant economic changes due to its oil wealth; however, this has not translated into equitable growth or substantial poverty reduction. The study aims to analyze the effects of inflation rates, tariffs, and literacy rates on economic development and poverty alleviation. Analytical methods include the Augmented Dickey-Fuller unit root test, cointegration test and First Difference ARDL model. The study reveals that despite generating substantial oil revenues, over 40% of Nigerians live below the poverty line, underscoring the phenomenon of the "resource curse." Furthermore, it identifies gaps in policy effectiveness, local community engagement, and long-term economic sustainability. By analyzing the relationship between oil production and socio-economic outcomes, this paper calls for targeted policy interventions that prioritize equitable wealth distribution and sustainable development strategies to mitigate poverty in Nigeria. The study emphasizes the need for economic diversification and balanced sectoral development to optimize economic potential and enhance welfare in Nigeria. [ABSTRACT FROM AUTHOR]

Copyright of Petroleum Geology & Oilfield Development in Daqing is the property of Editorial Department of Petroleum Geology & Oilfield Development in Daqing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Oil is one of the significant energy resources for the majority of the world’s states, so many of them monitor and analyze the price of black gold. Currently, there are such organizations of oil exporting countries as OPEC and OPEC+, which for a long time continue to influence not only the world market of this energy resource but also the events taking place in the economic and political spheres of the world. These organizations’ actions have a direct impact on market conditions, policy making, oil price, and the volume of its supply on the market in world trade. The collective responsibility of the member countries for a significant portion of global oil production makes the decisions and actions of OPEC and OPEC+ extremely important for the global oil industry and the economy as a whole. All the above-mentioned points to the relevance of the topic of the study, the objectives of which are to analyze the history of the emergence of the oil exporting countries’ organizations, the dynamics of their development during the history of their existence, as well as to assess the degree of their influence on the oil industry and the global economy as a whole.

Carbon dioxide (CO2) enhanced oil recovery (EOR) is considered to be an effective measure to increase oil productivity by injecting CO2 into reservoirs. Nevertheless, the injection of CO2 can potentially induce instability in discontinuities such as faults and fractures within the reservoir, influencing the safety and efficiency of the operation. Qualitative analysis of fault stability was implemented in the integrated process of CO2-EOR, by integrating fluid dynamics models, in-situ stress conditions and rock mechanics parameters. The results show that there is a pressure decreasing region around the oil producer, and CO2 injection has a prominent influence on reservoir pressure maintenance. The reservoir pressure and liquid flow of oil producer is slightly higher from the beginning of CO2 injection. The minimum effective normal stress and the maximum slip tolerance of the faults are aligned with the axis between the CO2 injector and the oil producer. The fault friction angle is the primary factor in discontinuity stability analysis, influencing the slip rate and mode during CO2-EOR. The larger the friction angle, the fewer faults are in the critical slip state. Fault stability analysis is a complete assessment, indicating that a fault may remain stable even if certain parts reach a critical state. [ABSTRACT FROM AUTHOR]

Higher concentrations of ambient air pollutants, including PM2.5 and NO2, and other pollutants have been found near active oil and gas wells and may be associated with adverse COVID‐19 outcomes. We assessed whether residential exposure to nearby oil and gas production was associated with higher rates of the respiratory infection COVID‐19 and related mortality using a population‐based ecological study in California. Using gridded population estimates, we estimated area‐level exposure to annual average oil and gas production volume from active wells within 1 kilometer (km) of populated areas within census block groups from 2018 to 2020. We geocoded confirmed cases and associated deaths to assess block group case and mortality rates from COVID‐19 from February 2020 to January 2021. We fit hierarchical Poisson models with individual and area covariates (e.g., age, sex, socioeconomic disadvantage), and included time and other interactions to assess additional variation (e.g., testing, reporting rates). In the first 4 months of the study period (February–May 2020), block groups in the highest tertile of oil and gas production exposure had 34% higher case rates (IRR: 1.34 95% CI: 1.20, 1.49) and 55% higher mortality rates (MRR: 1.52 95%: CI: 1.14, 2.03) than those with no estimated production, after accounting for area‐level covariates. Over the entire study period, we observed moderately higher mortality rates in the highest group (MRR: 1.16 95%: CI: 1.01, 1.33) and null associations for case rates. Plain Language Summary: Exposure to air, noise, light pollution and other localized stressors from active oil and gas drilling may affect the immune and cardiovascular systems and respiratory health, including diseases such as COVID‐19. This study reports on COVID‐19 case and death rates in communities within 10 km of active oil and gas production. We observed that California communities that were located less than 1 km from an actively producing oil and gas well were more likely to have higher COVID‐19 case and death rates in the first 4 months of the pandemic, especially when the level of production was high. Across our entire study time (February 2020–January 2021), we did not observe higher rates of cases or deaths in these communities, except for deaths in communities with the highest amount of production. These results suggest that if there is an effect of oil and gas production on COVID‐19 rates, it may be on the number of people that become severely ill; overall, it suggests that more research may help to understand why different communities had different levels of COVID‐19. Key Points: Using gridded population estimates, we estimated exposure to oil and gas production in areas within 1 km of an active wellWe observed higher reported case and mortality rates in areas with higher estimated oil and gas production from February to May 2020We geocoded COVID‐19 cases and deaths to census block groups and estimated age and sex‐specific mortality rates from February 2020 to January 2021 [ABSTRACT FROM AUTHOR]

The problem of 2D filtration flow in the neighborhood of a producing vertical fracture of limited size and finite conductivity is revisited. New asymptotic solutions specific of 2D inflows to a fracture at early times with pseudo-1D inflows, and at large times with pseudo-radial inflows, are obtained. In general, the problem does not allow for an exact analytical solution to be obtained for any time and any fracture conductivity, even using the Laplace transform. In the limiting cases, the equations are simplified and can be solved either exactly or approximately. The vertex solutions are then interpolated to construct an approximate solution for the profiles of pressure, flowrate and inflow along a fracture at any time and any fracture conductivity. The derived general solution is compared with the numerical solver and analytical solutions, previously obtained for limiting cases of infinite conductivity, steady and pseudo-steady-state flow regimes. The obtained approximation makes it possible to estimate the accurate solution of a fluid filtration problem much faster than numerical methods, while maintaining the accuracy sufficient for field operations. This makes the results of this work to apply to extensive multivariate simulations of fractured well production and inverse problems, such as the problem of optimization and interpretation of field data. [ABSTRACT FROM AUTHOR]

This study was an ex-port factor research that investigated the content of PAHs in the wetlands in Kolokolo and environs. The study answered 5 research questions and tested a hypothesis. To achieve these, the wetlands in the 5 settlements were mapped into 5 sampling grids of 50 meters apart and water samples were collected from 5 spots with 125mL plastic sampling bottles at 10cm depth and covered sub surface. The samples from each grid were bulked, composites drawn and fixed with HNO3 and stored in ice cooled flasks for analysis. The analytical standard adopted was EU 1881/2014 while the instrument of determination deployed was Agilent GC/MS Triple Quadruple model 7000. The mean result obtained were; pyrene 1.02 ± 0.01µg/l, chrysene, 1.02±0.01 µg/l, BaP; 1.03 ± 0.01µg/l BaA; 1.02 ±0.02ug/l and BbF, 1.03 ± 0.02µg/l. The mean results were subjected to test of significance with ANOVA using SPSS IBM model 29 at 0.05 level of significance and the p value was 0.042 thus rejecting Ho. The study concluded that the wetlands are contaminated with PAHs above EU 1881/2014 MPC for wetlands thus the produce are not fit for human and animal consumption. They are equally not exportable. The study recommended that the oil companies should be compelled to adopt world best practices in their operational activities, the monitoring agencies NESREA and NOSDRA should scale up their surveillance and the impacted ecosystem should be remediated and restored. [ABSTRACT FROM AUTHOR]

Idesia polycarpa Maxim is a high-value species of fruit oil with edible, abundant linoleic acid and polyphenols. Idesia polycarpa is described as a dioecious species, and the flowers are male; female and bisexual flowers are produced on separate plants. In order to explore the flower types of Idesia polycarpa, the morphology of its flowers and inflorescence were investigated in this study. The flower and inflorescence types, the diameter, and the flowering sequencing in male and female inflorescence were determined. We also detected the length, width, and fresh weight of leaves, shoots, and female inflorescence, as well as the length and fresh weight of the petiole during the development. Additionally, we compared the length, width, the length/width ratio, and the flowering density between 5- and 7-year-old female trees. The phenological period observation of Idesia polycarpa showed that the development process can be roughly divided into 12 stages, including bud burst, leaf expansion, inflorescence growth, initial flowering, full flowering, flower decline, initial fruiting, fruit enlargement, fruit color change, fruit ripening, post-ripening of fruit, and leaf fall periods. Furthermore, four elites' fruit determined the oil content and the composition of fatty acid content during the development. The dynamic of fatty acids contents, the palrnitic acid, palmitoleic acid, stearic acid, oleic acid, and linolenic acid contents were detected during the fruit development of four elites. Moreover, the mineral elements content of fruit of four elites during development were determined. The patterns of vegetative and reproductive growth in young dioecious trees of Idesia polycarpa provided the theoretical basis for artificial pruning and training. [ABSTRACT FROM AUTHOR]

The present article describes a method for determining the physico-mechanical properties of a synthesized batch of proppants. Industrial waste is one of the sources of anthropogenic impact on the environment on a global scale, being formed in the process of coal and oil extraction as a by-product.With the decrease in stocks of high-quality natural raw materials and the accumulation of man-made products, the problem of waste utilization becomes urgent. [ABSTRACT FROM AUTHOR]

Abstract 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.

Microbial enhanced oil recovery (MEOR) is a promising method for improving oil recovery from challenging reservoirs such as those found in Kazakhstan. MEOR relies on the activities of microorganisms to modify the properties of the reservoir, such as reducing the oil viscosity, increasing the reservoir permeability, and generating by-products that mobilize the oil. Implementing MEOR in Kazakhstan could lead to significant economic benefits for the country by increasing oil production and royalties from fossil fuel exports. Oil production in Kazakhstan has seen fluctuations in recent years, with 2018 recording a production level of 1.814 million barrels per day. Among regions, Atyrau region contributed the most to oil production with 23.4 million tons of oil. Following Atyrau, the Mangystau region produced 8.2 million tons, and Aktobe produced 2.4 million tons. Overall, the use of MEOR in Kazakhstan's oil fields could offer a promising solution for enhanced oil recovery, while minimizing environmental impact and cost. While specific data on the current use of MEOR in field conditions in Kazakhstan might be limited, the fact that studies are underway suggests a growing interest in applying this technology in the country's oil fields. It is exciting to think about the potential benefits these studies could bring to Kazakhstan's oil industry once their findings are implemented in field operations. These studies have significant implications for Kazakhstan's oil production in the future. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Information on associated gas flaring in the Niger Delta is analyzed to characterize the various stages in the lifecycle of an oil exploration and production facility through which gas flaring is introduced into an area, leading to ecological, health, and economic impacts, and possible policies and implementation strategies for the reduction of the flared gas are offered. Gas flaring is currently occurring at a rate of 5318 million m3 per year in the Niger Delta region. The impacts of gas flaring on the ecological, human, and economic systems include poor air quality, acid rain, and soil degradation. Other impacts include decreased crop yield, increased incidences of respiratory diseases amongst inhabitants in the area, and losses of billions of USD yearly in economic costs. Three dominant stages in the introduction of gas flaring are characterized in this study, using the concept of the management of the invasion of non-native species into an ecosystem and it is determined that the cheapest method of minimizing gas flaring is to incorporate mitigation measures during the design stage of the oil exploration/production facility, rather than after flaring has commenced, as is the common emphasis. During the early periods of oil production, gas flaring is largely localized, and the gas utilization measures can still be implemented to good effect. However, once the facility is established, gas flaring becomes pervasive, stretching kilometers beyond the flare points. Current policies like the imposition of flare-out years on the oil producers have helped, but they have been insufficient as the intensity of gas flaring in the region continues at double the average global levels. Working with relevant stakeholders, a realistic flare-out deadline should be agreed upon, clear and specific gas flaring legislation should be drawn up that includes measures to mitigate gas flaring for each proposed oil facility, and proper data collection and management services would enable the implementation of the policies to be based on robust evidence. These policies would shift the costs of gas flaring away from the inhabitants of the region back to the operators of the facilities that are the sources of the flares. [ABSTRACT FROM AUTHOR]

In accordance with the United Nations Sustainable Development Goals agenda for decent and sustainable economic growth highlighted in the UNSDGs-8, several economies over the years have been on the quest for drivers for decent and sustainable economic growth, of which the Arab bloc is no exception. To this end, the present study draws strength from the classical growth model while exploring the dynamic nexus between oil production and economic growth while accounting for other key growth drivers like gross capital formulation accumulation, labour, trade openness, and financial development for a balanced panel of selected Arab economies. To operationalise the study objectives, the present study leverages second-generational panel econometric approaches. The econometrics techniques applied circumvent the cross-sectional dependency and slope heterogeneity in the sampled bloc. For co-integration analysis, the Westerlund's panel co-integration test affirms a long-run equilibrium relationship between the study's outlined variables. Furthermore, for long-run estimates, the present study leverages the common correlated effects mean group (CCEMG) methodology and the augmented mean group (AMG) method for robustness and soundness of the results and coefficients. The present study corroborates the trade-induced growth hypothesis in the entire panel at a p < 0.001 statistical level, which resonates with the mercantilism school of thought. Additionally, the present study also affirms the Solow–Swan hypothesis, where gross capital formation accumulation and labour drive economic growth. Interestingly, the panel bloc shows that oil production is a key driver to the nation's economic growth, at a p < 0.05 statistical level. However, from a policy standpoint, there are policy suggestions for diversification of the Arab economies to move from a mono-economy dependent on oil production to other sectors like service, industry, and manufacturing, which require labour, capital accumulation, and more. Further policy caveats are outlined in the concluding section. [ABSTRACT FROM AUTHOR]

Abstract Higher concentrations of ambient air pollutants, including PM2.5 and NO2, and other pollutants have been found near active oil and gas wells and may be associated with adverse COVID‐19 outcomes. We assessed whether residential exposure to nearby oil and gas production was associated with higher rates of the respiratory infection COVID‐19 and related mortality using a population‐based ecological study in California. Using gridded population estimates, we estimated area‐level exposure to annual average oil and gas production volume from active wells within 1 kilometer (km) of populated areas within census block groups from 2018 to 2020. We geocoded confirmed cases and associated deaths to assess block group case and mortality rates from COVID‐19 from February 2020 to January 2021. We fit hierarchical Poisson models with individual and area covariates (e.g., age, sex, socioeconomic disadvantage), and included time and other interactions to assess additional variation (e.g., testing, reporting rates). In the first 4 months of the study period (February–May 2020), block groups in the highest tertile of oil and gas production exposure had 34% higher case rates (IRR: 1.34 95% CI: 1.20, 1.49) and 55% higher mortality rates (MRR: 1.52 95%: CI: 1.14, 2.03) than those with no estimated production, after accounting for area‐level covariates. Over the entire study period, we observed moderately higher mortality rates in the highest group (MRR: 1.16 95%: CI: 1.01, 1.33) and null associations for case rates.

Optimization of the “mature” fields development in machine learning algorithms is one of the urgent problems nowadays. The task is set to extend the effective operation of wells, optimize production management at the late stage of field development. Based on the task set, the article provides an overview of possible solutions in waterflooding management problems. Production management technology is considered as an alternative to intensification of operation, which is associated with an increase in the produciton rate and involves finding solutions aimed at reducing the water cut of well production. The practical implementation of the “Neural technologies for production improvement” includes the following steps: evaluation, selection, predictive analytics. The result is a digital technological regime of wells that corresponds to the set goal and the solution of the optimization problem in artificial intelligence algorithms using the software and hardware complex “Atlas – Waterflood Management”.“Neural technologies for production improvement” have been successfully tested at the pilot project site of the productive formation of the Vatyeganskoe field. The article provides a thorough and detailed analysis of the work performed, describes the algorithms and calculation results of the proxy model using the example of the pilot area, as well as the integration of the “Atlas – Waterflood Management” and the organization of the workflow with the field professionals of the Territorial Production Enterprise Povkhneftegaz.

The country needs new, profitable «here and now» reserves that can slow the rate of oil production decline. In this regard, the subsoil manager urgently needs to take fundamental measures to raise investment in oil prospecting and to speed up the process. All hopes rest upon independent investors who have potential to accelerate and increase prospecting activity. In order to stimulate oil prospecting, the subsoil manager needs to take several steps towards independent investors.

Rivers State, Niger Delta, Nigeria often referred to as the 'treasure bed of the nation' is the seat of crude oil production activities with the accompanying environmental degradation. The severity of the environmental pollution and contaminated air quality took a new turn for the worse in November 2016, when the residents of Port Harcourt city, Rivers State, a major oil producing State experienced for the first time, aerosol deposition of plumes of black soot. This systematic review paper is aimed at quantifying the severity of this public health challenge. Using appropriate search words, the following databases SCOPUS, PUBMED, Google Scholar, and AJOL were searched from 1990 to 2022 to enable comparative analyses of data before and after the emergence of black soot deposition. Air-related morbidities and mortalities such as cerebrospinal meningitis (CSM), chronic bronchitis, measles, pertussis, hemoptysis, cough, pulmonary tuberculosis, pneumonia, and upper respiratory tract infection (URTI), pneumonia, eye irritation, conjunctivitis, traumatic skin outgrowth, cancers, cardiovascular diseases, and child deformities were compared with levels of air pollutants and particulate matter. The results showed that Port Harcourt city's ambient air quality data were above the standard National Ambient Air Quality data and that of other regulatory agencies having higher levels of both inorganic and organic pollutants. There were significant relationships between air pollutants concentration with morbidities. These correlations were significant in the period covering 2016–2022. Consequently, it is concluded that the black soot emissions in Port Harcourt city, Nigeria has worsened the public health situation in the city. [ABSTRACT FROM AUTHOR]

In this study, a neural network model is developed for the prediction of oil flow rates in wells lifted by electrical submersible pumps (ESPs). Three attributes of the model in this work make this study unique. First, the knowledge on the computational cost of models has been presented, a rarity in most neural network models on this subject; second, the models have been explicitly presented, a feature uncommon in published ANN predictive modelling studies; and third, it includes a sensitivity analysis of input variables. The dataset utilized for the model development comprises 275 data points collected from ESP-lifted wells in the Middle East. Statistical evaluation of the model's performance using the metrics such as mean square error, root mean square error and coefficient of determination demonstrates high predictive accuracy with respective values of 0.0000201861, 0.00449 and 0.999. In order to ascertain the parametric importance of the inputs, Garson's algorithm was utilized. In this regard, choke size and upstream pressure had the highest influence (19% and 16%, respectively), while casing head pressure had the least effect (4.8%) on oil flow rate. In terms of memory requirements and processing speed for software applications, the model had a memory footprint of 888 bytes and required 191 multiply and accumulate operations to give an output. By utilizing the proposed models, the time-consuming separator tests measurements of flow rate would no longer be necessary and real-time results could be provided in the field. This work would be useful to production engineers who seek a quick and accurate means of estimating oil flow rate from ESP wells in real time. [ABSTRACT FROM AUTHOR]

The diversity of microalgae and bacteria allows them to form beneficial consortia for efficient wastewater treatment and nutrient recovery. This study aimed to evaluate the feasibility of a new microalgal-bacterial combination in the treatment of ice cream wastewater for biomass harvest. The bacterium Novosphingobium sp. ICW1 was natively isolated from ice cream wastewater and the microalga Vischeria sp. WL1 was a terrestrial oil-producing strain of Eustigmatophyceae. The ice cream wastewater was diluted 4 folds for co-cultivation, which was relatively less inhibitory for the growth of Vischeria sp. WL1. Four initial algal–bacterial combinations (v:v) of 150:0 (single algal cultivation), 150:1, 150:2, and 150:4 were assessed. During 24 days of co-cultivation, algal pigmentation was dynamically changed, particularly at the algal–bacterial combination of 150:4. Algal growth (in terms of cell number) was slightly promoted during the late phase of co-cultivation at the combinations of 150:2 and 150:4, while in the former the cellular oil yield was obviously elevated. Treated by these algal–bacterial combinations, total carbon was reduced by 67.5 ~ 74.5% and chemical oxygen demand was reduced by 55.0 ~ 60.4%. Although single bacterial treatment was still effective for removing organic nutrients, the removal efficiency was obviously enhanced at the algal–bacterial combination of 150:4. In addition, the harvested oils contained 87.1 ~ 88.3% monounsaturated fatty acids. In general, this study enriches the biotechnological solutions for the sustainable treatment of organic matter-rich food wastewater. [ABSTRACT FROM AUTHOR]

Oilfield production is controlled by a wide range of geological and engineering parameters, many of which are at least partially interrelated. This paper uses multivariate statistical methods (principal component analysis, regression analysis and analysis of variance) to determine how these parameters are related, and which of them are most significant in controlling and predicting oilfield performance. The analysis is based on a database of publicly available oilfield data from the United Kingdom Continental Shelf (UKCS), from which a series of geological, engineering and fluid‐related control variables from 136 fields were pre‐processed and analyzed. This dataset is a subset of a much wider project database for UKCS oil, gas and condensate fields. For this study, the project database was divided into two datasets: a first dataset with 10 parameters from 136 fields, and a second, more detailed dataset with 27 parameters from 38 fields. Both datasets were analysed using principal component analysis in order to investigate possible correlations between numerically/statistically interrogable predictor variables such as porosity, permeability, number of production wells, gas‐oil ratio and reservoir temperature. A regression analysis was then carried out on the predictor variables in order to obtain a ranking of predictability (i.e. how indicative a predictor is of a particular outcome) and sensitivity (how sensitive an outcome is to slight changes in a predictor) in relation to recovery factor based on R‐squared and regression coefficient values. The results showed that key variables from the principal component analysis included field size, number of production wells, PVT, gross depositional environment and reservoir quality. High‐ranking parameters of predictability and sensitivity from the regression analysis were found to include API, net‐to‐gross, porosity and reservoir depth. These results are consistent with previous studies and suggest that it should be possible to forecast oilfield recovery based on only a few selected input variables. As a preliminary test of forecasting ability of the variable permutations put forward, a best‐subsets multiple regression was carried out using a statistical software package and yielded results which corroborated the main findings. [ABSTRACT FROM AUTHOR]

Copyright of Brazilian Journal of Law & International Relations / Relações Internacionais no Mundo is the property of Relacoes Internacionais no Mundo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The main objective of the present study is to examine the determinants of greenhouse gas emissions in Canada using panel data of 10 provinces from 1990 to 2019. The pooled ordinary least squares method is used to estimate the models. The main findings of the basic model show that provinces with larger populations, younger ages, and more income produce higher levels of greenhouse gas emissions. The results of the extended model (per capita greenhouse gas emissions as the dependent variable) show that only five factors (out of ten potential determinants identified)—oil production per capita, gas production per capita, motor vehicles registered per capita, electricity generation intensity, and heating degree days—are significant determinants of per capita greenhouse gas emissions. The results also reveal that the provinces with older populations have lower per capita greenhouse gas emissions in Canada. However, both trend variables played an important role in explaining the greenhouse gas emissions per capita in Canada. Moreover, there were no significant differences among the patterns of the per capita greenhouse gas emissions in Canada after 2005. [ABSTRACT FROM AUTHOR]

A new generation of oilfield equipment capable of safe operation for a long period in challenging conditions has appeared in recent years. In that context, it is of great interest to create high-quality materials with excellent mechanical properties and performance and to develop economical high-speed methods of producing such materials. The present work focuses on the advantages and disadvantages of current technologies and materials for the production of borehole pumping equipment and on recommendations regarding the selection of high-performance pumping equipment and its operating conditions. [ABSTRACT FROM AUTHOR]

Copyright of Iraqi Journal of Chemical & Petroleum Engineering is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Microbial enhanced oil recovery (MEOR) is a promising method for improving oil recovery from challenging reservoirs such as those found in Kazakhstan. MEOR relies on the activities of microorganisms to modify the properties of the reservoir, such as reducing the oil viscosity, increasing the reservoir permeability, and generating by-products that mobilize the oil. Implementing MEOR in Kazakhstan could lead to significant economic benefits for the country by increasing oil production and royalties from fossil fuel exports. Oil production in Kazakhstan has seen fluctuations in recent years, with 2018 recording a production level of 1.814 million barrels per day. Among regions, Atyrau region contributed the most to oil production with 23.4 million tons of oil. Following Atyrau, the Mangystau region produced 8.2 million tons, and Aktobe produced 2.4 million tons. Overall, the use of MEOR in Kazakhstan’s oil fields could offer a promising solution for enhanced oil recovery, while minimizing environmental impact and cost. While specific data on the current use of MEOR in field conditions in Kazakhstan might be limited, the fact that studies are underway suggests a growing interest in applying this technology in the country’s oil fields. It is exciting to think about the potential benefits these studies could bring to Kazakhstan’s oil industry once their findings are implemented in field operations. These studies have significant implications for Kazakhstan’s oil production in the future.

Abstract In this study, a neural network model is developed for the prediction of oil flow rates in wells lifted by electrical submersible pumps (ESPs). Three attributes of the model in this work make this study unique. First, the knowledge on the computational cost of models has been presented, a rarity in most neural network models on this subject; second, the models have been explicitly presented, a feature uncommon in published ANN predictive modelling studies; and third, it includes a sensitivity analysis of input variables. The dataset utilized for the model development comprises 275 data points collected from ESP-lifted wells in the Middle East. Statistical evaluation of the model’s performance using the metrics such as mean square error, root mean square error and coefficient of determination demonstrates high predictive accuracy with respective values of 0.0000201861, 0.00449 and 0.999. In order to ascertain the parametric importance of the inputs, Garson’s algorithm was utilized. In this regard, choke size and upstream pressure had the highest influence (19% and 16%, respectively), while casing head pressure had the least effect (4.8%) on oil flow rate. In terms of memory requirements and processing speed for software applications, the model had a memory footprint of 888 bytes and required 191 multiply and accumulate operations to give an output. By utilizing the proposed models, the time-consuming separator tests measurements of flow rate would no longer be necessary and real-time results could be provided in the field. This work would be useful to production engineers who seek a quick and accurate means of estimating oil flow rate from ESP wells in real time.

The jet pump is an artificial lift employed when the reservoir pressure declines and the well deviation increases. The use of computer well models for optimizing the oil well output has proven to be a successful strategy, and has helped increasing the efficiency and production of numerous wells. The objective of this study was to use a production optimization technique that achieves some improvements, and recommend approaches toward increasing the oil well production. The effects of the motive fluid flow rate and pressure on the oil production rate were investigated to determine the optimal injection rate and pressure on the performance of the deep well water-oil axial jet-pump. Additionally, the effects of the well-head pressure, water cut, and roughness of tubing on oil production of this jet pump type were investigated. The results revealed that the impact on the oil lift performance is significant. The oil production increased by 19.43%, and the optimal economic value for the injection rate and pressure for the GA-1A well are 744.44 BFPD and 2722.22 psig, respectively. In summary, increasing the tubing roughness decreased the well's total liquid production. Thus, maintaining the well integrity is a very important factor because not doing so can lower the productivity by up to 20%–25%.

The relevance of the study is due to the problem that is typical for different types of structures of screw press zeer corps, namely, determining the optimal gap for oil yield, which has practical and economic feasibility. In this regard, this study is aimed at analysing the existing types of zeer corps, identifying their advantages and disadvantages to find methods to improve their design and increase oil yield. The leading methods for solving this problem are empirical research methods, which allow comprehensively considering the existing types of structures based on observation and, through comparison and experiment, to find a rational solution to the problem. The paper analyses the features of technical means for oil separation in presses and extruders, substantiates the practicality of the existing design and indicates the complexity or simplicity of designs in the scientific literature. The need to supplement the existing terms for various designs of the oil separator bodies and possible ways to improve the process of oil separation into different fractions are identified. Experimental studies were carried out with a set of semi-hulls of the zeer sections with different gaps. This made it possible to identify a smaller percentage of cake shedding through the zeer sections, with a corresponding reduction in the gap. The results of oil yield were obtained depending on the established gap in the semihulls of the slotted elements of the zeer camera and the heating temperature of the hulls. A decrease in the percentage of shedding with a decrease in the gap in the zeer camera was found. The studied design of the zeer camera type confirmed the versatility and simplicity of its design, which facilitates its maintenance and replacement. For each processed tonne of seeds, due to the increase in the amount of oil squeezed out, the profit of a farmer or enterprise that improves twin-screw extruders by adjusting the gaps as follows will increase accordingly

Idesia polycarpa Maxim is a high-value species of fruit oil with edible, abundant linoleic acid and polyphenols. Idesia polycarpa is described as a dioecious species, and the flowers are male; female and bisexual flowers are produced on separate plants. In order to explore the flower types of Idesia polycarpa, the morphology of its flowers and inflorescence were investigated in this study. The flower and inflorescence types, the diameter, and the flowering sequencing in male and female inflorescence were determined. We also detected the length, width, and fresh weight of leaves, shoots, and female inflorescence, as well as the length and fresh weight of the petiole during the development. Additionally, we compared the length, width, the length/width ratio, and the flowering density between 5- and 7-year-old female trees. The phenological period observation of Idesia polycarpa showed that the development process can be roughly divided into 12 stages, including bud burst, leaf expansion, inflorescence growth, initial flowering, full flowering, flower decline, initial fruiting, fruit enlargement, fruit color change, fruit ripening, post-ripening of fruit, and leaf fall periods. Furthermore, four elites’ fruit determined the oil content and the composition of fatty acid content during the development. The dynamic of fatty acids contents, the palrnitic acid, palmitoleic acid, stearic acid, oleic acid, and linolenic acid contents were detected during the fruit development of four elites. Moreover, the mineral elements content of fruit of four elites during development were determined. The patterns of vegetative and reproductive growth in young dioecious trees of Idesia polycarpa provided the theoretical basis for artificial pruning and training.

Salt lakes are significant components of global inland waters. Salt lake (SL) water can provide precious mineral resource for microbial growth. The prospect of utilizing diluted SL water for cultivation of a terrestrial oil-producing microalga Vischeria sp. WL1 was evaluated under laboratory conditions. Based on the detected mineral element composition, the water from Gouchi Salt Lake was diluted 2, 4, 6 and 8 folds and used with supplementation of additional nitrogen, phosphorus and iron (SL+ water). It was found that 4 folds diluted SL+ water was most favorable for biomass and oil production. When cultivated in this condition, Vischeria sp. WL1 gained a biomass yield of 0.82 g L−1 and an oil yield of 0.56 g L−1 after 24 days of cultivation, which is comparable to the optimum productivity we previously established. In addition, total monounsaturated fatty acid contents (64.4∼68.1 %) of the oils resulted from cultures in diluted SL+waters were higher than that in the control (55.5 %). It was also noteworthy that in all these cultures the oil contents (652.0∼681.0 mg g−1) accounted for the most of the biomass, which are far more than the protein and starch contents. This study demonstrates the feasibility of using SL water as a cost-effective mineral resource to cultivate microalgae for biomass and oil production.

This study investigates the well named X (for confidential reasons) of the field called Y which initially was productive with the natural energy of the reservoir of the oil in the absence of water. After a few years of production, water began to overflow excessively in the well. The goal of this paper is to maximize the oil production in an oil well X by reducing water ingress. The Pressure Volume Temperature (PVT) data, completion data, and reservoir data are analyzed via PIPESIM and Excel software by using the nodal analysis method to get the well performance and decline curve for predictions. Two scenarios are considered: firstly, to install an electric submersible pump (ESP) to activate the X well and secondly to make a new perforation. The ESP is installed at 11300 ft where the water production flow rate is 5586.264 STB/d and the oil production flow rate is 1396.566 STB/d. The new perforation is installed at 12038 ft where the water production flow rate is 277.1693 STB/d and the oil production flow rate is 5543.387 STB/d. To have the optimal parameters, the sensitivity analysis is applied to the flowline diameter and the wellhead pressure. The optimal parameter values obtained are 308.6128 STB/d for the water production flow rate and 5863.643 STB/d for the oil production flow rate. The new perforation is appropriate because this scenario allows water reduction, oil production maximization, profitability of 98086854 $, and a return on investment in 5 months during 16 years of production.

Polyethylene is the type of waste plastic that accounts for the most significant proportion of municipal solid waste. Waste polyethylene can be valorized via pyrolysis and produce value-added oil, gas, and char. On the other hand, self-sustaining smoldering is an emerging technical means to deal with sand/soil contaminated by organic matter. The high-temperature heat generated by smoldering can be used as a heat source for pyrolyzing waste polyethylene. Therefore, this study investigates numerically the pyrolysis of waste polyethylene driven by self-sustaining smoldering. A novel 4-step lumped kinetic model is proposed for simulating the pyrolysis of waste polyethylene. The results indicate that the operating parameters can determine the pyrolysis product yields by regulating the pyrolysis temperature and the volatile residence time. Note that higher temperatures and longer residence times favor the generation of shorter-chain pyrolysis products because of the intensified volatilesʼ secondary cracking. It can be concluded that a high interface-wall heat transfer coefficient (400 W m−2 K−1), a low PE content (0.20), a high char concentration (2.4%), and a moderate air velocity (0.040 m s−1) are beneficial to oil yield. To some extent, this study may broaden the boundaries for the application of self-sustained smoldering-driven pyrolysis. [ABSTRACT FROM AUTHOR]

Optimal operation of petroleum production is important in a transition from energy systems based on fossil fuel to sustainable systems. One sub-process in petroleum production deals with transport from the (subsea) well-bore to a topside separator. Good control design for such operation requires a dynamic model of the petroleum flow from the well-bore to the separator. Here, such a dynamic model is considered for liquid production (oil/water) using an electric submersible pump (ESP) to aid in counteracting gravity and friction forces. Based on an existing model used for industrial control design, one goal is to report a complete dynamic model in a single paper. Emphasis is put on dimensionless equipment models for the simple change of units, and the model is developed from physical laws for easy replacement of sub-models, if needed. All the necessary information (equations, parameters) for model implementation is provided, and two candidate equation-based modeling languages are selected and compared: Modelica and ModelingToolkit [MTK] for Julia. The simulation results are virtually identical for the two languages and make sense from physics; however, there is a minor discrepancy in one plot—likely caused by slight differences in accuracy in handling initialization in the implicit algebraic equations. The implementation structures of the model in Modelica and MTK are similar. Modelica is a mature and excellent modeling tool, handles large-scale models, and has tools for producing C code and integration with other tools. MTK is still in rapid development, supports more model types than Modelica, and is integrated in an eco-system with excellent support for control design, optimization, model fitting, and more. To illustrate the suitability of using the developed model for control design, a simple PI controller is designed within the eco-system of MTK/Julia. [ABSTRACT FROM AUTHOR]

Sucker-rod deep-well pumping units widely used in oil production are described. It is shown that oil production depends on the operating conditions of these units, which are selected based on the results of analyzing closed dynamometer charts. The latter describe the load on the suspension depending on the stroke of the polished rod of the unit. The quality of preparing the charts determines the ability to diagnose the technical condition of the unit. The trends in the development of existing dynamometer systems and methods for diagnosing the condition of a sucker-rod deep-well pumping unit have been analyzed. One of the ways to create an intelligent intertraverse dynamograph is considered based on a messdose of a pocket dynamograph with the use of modern pressure, acceleration, and temperature sensors; STM32 controllers; a graphic liquid crystal display with an I2C interface; radio communication protocols and digital technologies for processing periodic sensor signals. The existing dynamometer systems along with force and stroke sensors installed in various unit locations were analyzed, and the possibility of developing an intelligent stationary dynamograph by utilizing the latest advances in the field of technology and equipment for analyzing noises of the measured signals has been demonstrated. The proposed dynamograph should ensure early diagnostics of the technical condition of the unit, while satisfying the following criteria: low cost; ease of assembly; high sensitivity, reliability, flexibility, and accuracy. A block diagram of an intelligent intertraverse dynamograph for a sucker-rod deep-well pumping unit is presented, which is based on a pocket dynamograph messdose. The proposed intelligent intertraverse dynamograph will be useful for early diagnostics of the technical condition of deep-well pumps and tubing strings connecting them with the ground equipment, which will ultimately contribute to improving reliability of oil production equipment. The proposed intelligent intertraverse dynamograph can also be used in other engineering fields, where there is a need to measure force. [ABSTRACT FROM AUTHOR]

This paper presents an approach for optimizing the oil recovery factor by determining initial oil production rates. The proposed method utilizes the Q-learning method and the reservoir simulator (Eclipse 100) to achieve the desired objective. The system identifies the most efficient initial oil production rates by conducting a sufficient number of iterations for various initial oil production rates. To validate the effectiveness of the proposed approach, a case study is conducted using a numerical reservoir model (SPE9) with simplified configurations of two producer wells and one injection well. The simulation results highlight the capabilities of the Q-learning method in assisting reservoir engineers by enhancing the recommended initial rates. [ABSTRACT FROM AUTHOR]