Oil Production Research Articles

Roles of Catalysts and Feedstock in Optimizing the Performance of Heavy Fraction Conversion Processes: Fluid Catalytic Cracking and Ebullated Bed Vacuum Residue Hydrocracking

Petroleum refining has been, is still, and is expected to remain in the next decades the main source of energy required to drive transport for mankind. The demand for automotive and aviation fuels has urged refiners to search for ways to extract more light oil products per barrel of crude oil. The heavy oil conversion processes of ebullated bed vacuum residue hydrocracking (EBVRHC) and fluid catalytic cracking (FCC) can assist refiners in their aim to produce more transportation fuels and feeds for petrochemistry from a ton of petroleum. However, a good understanding of the roles of feed quality and catalyst characteristics is needed to optimize the performance of both heavy oil conversion processes. Three knowledge discovery database techniques—intercriteria and regression analyses, and artificial neural networks—were used to evaluate the performance of commercial FCC and EBVRHC in processing 19 different heavy oils. Seven diverse FCC catalysts were assessed using a cascade and parallel fresh catalyst addition system in an EBVRHC unit. It was found that the vacuum residue conversion in the EBVRHC depended on feed reactivity, which, calculated on the basis of pilot plant tests, varied by 16.4%; the content of vacuum residue (VR) in the mixed EBVRHC unit feed (each 10% fluctuation in VR content leads to an alteration in VR conversion of 1.6%); the reaction temperature (a 1 °C deviation in reaction temperature is associated with a 0.8% shift in VR conversion); and the liquid hourly space velocity (0.01 h-1 change of LHSV leads to 0.85% conversion alteration). The vacuum gas oil conversion in the FCC unit was determined to correlate with feed crackability, which, calculated on the basis of pilot plant tests, varied by 8.2%, and the catalyst ΔCoke (each 0.03% ΔCoke increase reduces FCC conversion by 1%), which was unveiled to depend on FCC feed density and equilibrium FCC micro-activity. The developed correlations can be used to optimize the performance of FCC and EBVRHC units by selecting the appropriate feed slate and catalyst.

Biochar improves morpho-physiological growth, osmolyte accumulation, nutrients balance, anti-oxidative defense and oil productivity of Brassica under flooding stress

Soil flooding is a serious abiotic stress that can repress plant growth and yield. The intensity of flooding stress is continuously increasing owing to rapid climate change and changes in rain intensity and frequency. Biochar (BC) emerges as an important soil amendment to mitigate adverse impacts of abiotic stress. The role of BC against different stresses is well reported, however, its role under flooding stress is not determined yet. Thus, this experiment was conducted to determine the role of BC on the performance of brassica crops under flooding stress. The experiment was comprised of well-watered (WW) and flooding stress (FS) conditions and biochar application: control, 1% biochar, and 2.5% biochar. The results indicated that flooding stress stunted the plant growth and impaired the photosynthetic pigments, leaf water status, osmolytes yield and yield traits, and oil concentration and increased the electrolyte leakage (EL), hydrogen peroxide (H2O2) and malondialdehyde (MDA) concentration. The application of BC at the rate of 2.5% mitigated the adverse impacts of salinity and upgraded the antioxidant activities (~50-120%), reduced the oxidative stress markets (~70-300%), and increased the leaf water status, photosynthetic pigments, osmolyte accumulation, nutrient uptake, yield traits, and oil contents. In conclusion, BC application can improve the productivity and oil yield of brassica under drought stress by improving plant physiological and biochemical functioning. However, more in depth studies are direly needed to explore the mechanism of BC to induce flood tolerance.

Numerical model of asphaltene deposition in vertical wellbores: Considerations of particle shape and drag force

Asphaltene deposition and plugging are common phenomena during crude oil production, significantly reducing production efficiency. Understanding the deposition behavior of asphaltene particles in vertical wellbores, particularly in relation to drag force interactions and settlement velocity, is imperative to mitigate these issues. Existing empirical models often fail due to their inherent inaccuracies and neglect of asphaltene particles' irregular shapes. This work established a quantitative method to describe irregular geometries of asphaltene particles. Shape coefficient, ∅, and shape coefficient influence factor, θ, are used to assess the impact of particle shape on the drag force coefficient and settling velocity. Experimental results from sedimentation experiments reveal particles with smaller shape coefficients encounter greater flow resistance and higher drag force coefficients. Moreover, the impact of shape coefficient on the drag coefficient gradually decreases as the Reynolds number increases. Based on these experimental findings, distinct models for the drag force coefficient and settling velocity of asphaltene particles are established, achieving a reduction in average error ranging between 2 % ∼ 25 % compared to existing models.

Application of smart proxy model for multi-optimization of CO2-EOR design in farnsworth unit with production-injection well conversion

CO2-Enhanced Oil Recovery (CO2-EOR) is an effective development strategy and an economically viable CO2 storage method for a mature oil field. In this study, a smart proxy model (SPM) was constructed to establish the optimal development strategies in Farnsworth Unit (FWU) considering CO2 storage and oil production with the production-injection well conversion. An SPM was constructed with the results of 16 reservoir simulations and was validated with an R2 values of 96.3 % and 97.5 % for the CO2 storage and oil production, respectively. The obtained Pareto front indicates a range of the optimized CO2 storage and oil production. In addition, the maximum CO2 storage case shows 260 % and 61.1 % of the CO2 storage and oil production of the base case, respectively. When the maximum oil production is targeted, the CO2 storage and oil production are respectively 66.5 % and 111.3 % of the base case. It was concluded that the SPM is effectively applicable for multi-objective optimization with fewer simulation runs and shorter time. In addition, the well conversion is a viable method to improve both the CO2 storage and oil production in the FWU during CO2-EOR process.

Examining macroeconomic factors and environmental sustainability: An OLS regression analysis of the impact of exports, imports, governmental budget, and oil products on CO2 emissions in Jordan

This study aims to investigate the relationship between macroeconomic factors and CO2 emissions. The study used a sample of data covering the period from 1991 to 2019 and employed ordinary least squares (OLS) method to estimate the relationship. The study found that there is a strong relationship between CO2 emissions and the macroeconomic factors of exports, imports, governmental budget, and oil products. The R-squared value of 0.717668 suggests that these variables explain approximately 72% of the variation in CO2 emissions. The coefficients for exports, imports and oil products are statistically significant at the 5% level. A negative coefficient for exports indicates that an increase in exports is associated with a decrease in CO2 emissions. On the other hand, a positive coefficient for imports suggests that an increase in imports is associated with an increase in CO2 emissions. Additionally, the positive coefficient for oil products indicates that an increase in oil product consumption is associated with a significant increase in CO2 emissions. The coefficient for the government budget variable is not statistically significant, which suggests that changes in the government budget do not have a significant impact on CO2 emissions. The results are robust and reliable as the assumptions of linearity, normality and homoscedasticity of errors were met. The study results could help policy makers in taking potential actions to mitigate CO2 emissions in the country.

Research on the Compounding Scheme of High-Efficiency and Environmentally Friendly Water-Based Well Cleaning Fluid and Analysis of Its Application Effect

In the process of oil well production, the deposition and enrichment of heavy oil and wax are common phenomena. The deposition of these high-viscosity organic substances will not only seriously affect the normal production of oil wells but also cause certain pollution to the environment. Traditional well-washing operations usually rely on high temperatures and strong cleaning chemicals, which have the problems of low cleaning efficiency at low temperatures and poor environmental protection. Therefore, it is particularly important to study a more efficient and environmentally friendly water-based well-washing fluid. At present, most oilfields in China use diesel or organic cleaning agents to clean oil wells, which not only increases the cost of well-washing operations but also may cause pollution to the environment. In response to this problem, the core of this study lies in its innovative compounding scheme. The scheme includes preferred alkaline components, surfactants, emulsifiers, and solubilizers, and introduces glass fiber cutting and erosion technology. This well-washing fluid can effectively remove wax and heavy oil attached to the well wall at a lower temperature, which not only improves cleaning ability but also greatly reduces the dependence on high temperature. The water-based well-washing fluid provided in this study is composed of water, alkaline substances, surfactants, emulsifiers, and glass fibers. Emulsifiers such as Tween 80, OP-20, and polyethers form a stable emulsification system to help disperse and encapsulate oil and grease particles.

Potential application of generative artificial intelligence and machine learning algorithm in oil and gas sector: Benefits and future prospects

With the rapid advancement of technology and societies, the global energy sector now acknowledges that by integrating contemporary digital technologies into their operations and capabilities, can improve their competitive advantage and innovation performance and processes. Moreover, energy operators are also facing a significant undertaking: how to best use and secure large amounts of data that promote sustainable productivity performance and minimise potential threats in the oil and gas value chain and project operations. In view of the foregoing, various facets like Generative Artificial Intelligence (GAI) and Machine Learning Algorithms (MLA) are increasingly gaining popularity within oil and gas sector operations. Thus, we explored how GAI and ML algorithms can enhance oil and gas value chain productivity performance. The Principal Component Analysis (PCA) was employed to identify significant GAI and MLA variables influencing performance in the oil and gas value chain, while Structural Equation Modelling (SEM) was used to test regression equations related to their application. The study found that risk portfolios and profiles can be appraised throughout the value chain by effectively utilising GAI and ML algorithms in upstream, midstream and downstream undertakings. While these findings are noteworthy and have significant implications for current practice, the paper advocates that an array of digital technologies beyond GAI and ML can still be examined during future studies to demonstrate a holistic perspective on how digital transformation can be achieved across the energy sector value and project operations.

Analysis of the bending performance of unbonded flexible risers

ABSTRACT As the key equipment for offshore oil and gas production systems, the unbonded flexible riser (UFR) is subjected to extensive interlayer and intralayer non-linear contact and slip that make it difficult to analyse its bending performance. In this paper, by combining the theoretical model of bending of the UFR with the finite element model, the influence of the number, width, external pressure and coefficient of friction of tensile armour wires on its bending performance was studied. The results showed that the non-slip bending stiffness of the UFR decreased by 3.20 and 23.35 kN·m2 every time one of the outer tensile armour wires was removed and the width of the wires was reduced by 0.3 mm, respectively. The external pressure and coefficient of friction did not influence its bending stiffness in the non-slip and complete slip stages, and were linearly related to the curvature of the critical slip.

Interplay of phenolic compounds and gene expression in phenylpropanoid and flavonoid pathways during olive (Olea europaea L.) ripening of ‘Leccino’ cultivar

This study presents a detailed analysis and interplay of the phenolics, relative gene expression and quality parameters during ripening of ‘Leccino’ olive fruit pulp and skin at seven maturity indexes, in the phenylpropanoid and flavonoid pathways. Tissue-specific gene expression analysis revealed statistically higher expression levels for eight genes in the skin. The only exception was anthocyanidin synthase (ANS), which expression level was statistically higher in the pulp. Our results confirm that the important role in olives of the anthocyanin composition have flavonoid 3′-hydroxylase (F3′H) and flavonoid-3′,5′-hydroxylase (F3′5′H) in both tissues. The phenolic content was mostly statistically higher in the skin than in the pulp and generally increased in both tissues during ripening. A notable shift in phenolic compounds occurs between maturity index 3 and 4, when the skin of the fruit turns completely purple. Results from this study highlight the intricate dynamics of physiological processes and biochemical mechanisms in the phenylpropanoid and flavonoid pathways in olive fruit. The findings also underscore the relationship between phenolic content, relative gene expression, and quality parameters, particularly in relation to color development during ripening in different olive fruit tissues. Our conclusions can be used by growers to improve the quality of fruit and consequently the quality of olive oil or other final products.

A Mini Review on the Opportunities for Membrane Pervaporation Technology for Energy-efficient Removal of Dispersed Oil and Dissolved Hydrocarbons from Produced Water

Produced water is reported to have the largest volume of waste stream associated with hydrocarbon recovery. It was estimated to increase from 250 million B/D in 2007 to more than 300 million B/D between 2010 and 2012. Market research conducted by Adroit put the globally produced water treatment market at a value of USD 5.10 billion in 2022. This value is anticipated to be USD 9.80 billion in 2032 at a compound annual growth rate (CAGR) of 5.80% over the prediction period. Oil and gas companies have been mandated to comply with the newly enacted environmental regulations that require extensive treatment of this water before discharge or reuse. The limited quantity of freshwater resources coupled with the increasing oil and gas production activities has made it necessary for all stakeholders to look for sustainable management of this water. Presently, a certain percentage of produced water is reused while the rest is discharged into the ocean. In both cases, the water needs to be thoroughly treated. The choice of technologies for produced water treatment depends on numerous factors, such as the chemical composition of the water and the level of purity that must be attained before disposal, recycling, or re-use. Some of the technologies used for produced water treatment include physical separation methods such as gravity, adsorption, filtration, coalescence, cyclones, flotation, centrifuges, membranes, and oxidation. There are also chemical and biological separation methods. Contaminants such as small droplets of dispersed oil and dissolved hydrocarbons (DODHs) are very challenging to remove using the above-listed water treatment technologies. Moreover, the use of membrane technology has been limited only to the use of reverse osmosis and membrane filtration for removing salinity, metals, and other inorganics. This article highlights the opportunities for the use of membrane vapor permeation and pervaporation for the removal of the small droplets of DODHs, which have been reported to be very challenging contaminants to remove. The use of 3D printing technology for the fabrication of membrane materials was reviewed. The 3D membrane development method can be used to fabricate almost any shape of the material in a highly customized manner using computer-aided design. The information presented in this article will serve as a useful reference for the technologies used for a sustainable water treatment strategy in the oil and gas industry.

Using palm oil residue for food nutrition and quality: from palm fatty acid distillate to vitamin E toward sustainability.

Increasing global palm oil production yields a valuable palm fatty acid distillate (PFAD) - a rich vitamin E (Vit-E) source and multifunctional ingredient in the food agro-industry - that can be utilized to achieve sustainability. This article reviews trends in the use and role of PFAD and its Vit-E in the food sector and proposes an integrated agro-industrial concept toward sustainability. Vit-E can be separated from PFAD with diverse and impactful pharmaceutical activities, including antioxidant, anti-inflammatory, anticancer and anti-ultraviolet effects. Based on in vivo experimental tests, PFAD and Vit-E supplementation can enhance the productivity and quality of livestock-based food products. PFAD is a plasticizer and antistatic packaging material in food packaging systems, and its derivatives can be used as food additives. Meanwhile, the Vit-E molecule in packaging can extend food shelf life by maintaining color stability, reducing lipid oxidation and rancidity, adding antimicrobial properties, and influencing changes in packaging properties such as water vapor, tensile strength, melting point and other physical properties. Toward sustainability, an integrated agro-industrial design has been proposed to implement clean production, increase the added value of palm oil industry residues, minimize environmental risks and increase profits to achieve long-term social welfare. In conclusion, PFAD residues and their Vit-E content have shown broad benefits in the food sector and prospects toward sustainability. © 2024 Society of Chemical Industry.

Non-specific Phospholipase C4 Improves Phosphorus Remobilization From Old to Young Leaves in Camelina.

Camelina sativa is regarded as a low-input oilseed crop for versatile food, biofuels and industrial applications with potential production on marginal lands, whereas phosphate (Pi) deficiency greatly reduces camelina seed production. To improve camelina resilience to low P conditions, here we overexpressed the Pi deficiency-induced non-specific phospholipase C4 (NPC4) to test its effect on camelina seed production under different levels of Pi availability. NPC4-overexpressing (OE) plants displayed increased seed yield and oil production, with a greater magnitude of increases under Pi-deficient than Pi-sufficient conditions. NPC4-OE camelina had a higher level of total P and free Pi in young leaves but a lower level in old leaves than in wild-type plants. More Pi was moved from old leaves to young leaves in NPC4-OE than in wild-type plants. NPC4-OE increased the expression of Pi transporter genes, and the increase was greater in old leaves and under Pi-deficient conditions. These data indicate that NPC4 improves camelina growth by promoting Pi remobilization from old to young tissues, revealing a mechanism by which NPC4 mediates plant response to Pi deficiency.

Sorbents based on foamed phosphate glass for collecting petroleum oil products from contaminated soils and water surfaces

Relevance. The need to clean from pollution soils and water areas contaminated with oil and chemical industry wastes. Physico-chemical methods are one of the effective ways of cleaning, provided that sorbents are applied in time to collect contaminants from the surface of water areas and landscapes. Sorption is the most efficient and cost-effective method for relatively small scale pollution. Despite the variety of existing sorbents, in most cases when cleaning up accidental spills, first of all, economic benefits and oil capacity value of the sorbent are guided. However, such essential criteria as: 1) main purpose (type of polluted surface and nature of pollution); 2) physical and chemical properties, including structural characteristics and acid-base adsorption centers; 3) peculiarities of oil or other pollutants adsorption. Taking into account these factors, it is possible to develop and improve the formulation of sorbents based on phosphate foams. Introduction of various modifying additives into material composition is likely to expand their field of application. Aim. Development of formulation and technological features of obtaining new phosphate sorbents in relation to their intended purpose: for collecting oil and petroleum product spills from soil or water surfaces. Methods. Gravimetric, microscopic spectroscopic, statistical and comparative methods. Results and conclusions. The authors have compared sorbents no. 1 and 2 in terms of physical and chemical properties, morphology and cleaning efficiency. Based on our laboratory studies, we concluded that sorbent no. 1 is better suited for sorption from aqueous surfaces and sorbent no. 2 is better suited for soil cleaning. Both sorbents have the potential to improve their technological properties. This allows refining the formulation of these materials with further testing in laboratory and field conditions, for example, at oil spill sites. For this purpose, it is possible to change the material composition using a different foaming agent, applying modifying additives and varying the temperature mode of firing. Development of new compositions and methods of sorbent foaming will make it possible to select optimal characteristics for each type of contamination. The author proposed as well to create phosphate biosorbent obtained by immobilization of fungi and bacteria on the surface of highly porous carrier. In this case, after sorption of pollution, adsorbed substances will undergo biodegradation with the formation of safe products, and the sorbent will perform the role of fertilizer.

Application of iron oxide nanoparticles improves growth and phytochemical constituents of in vitro cultured Carum copticum L.

Iron oxide nanoparticles (FeONPs) are widely used in various applications, such as biomedicine, environmental remediation, and agriculture. Moreover, FeONPs can affect the production of secondary metabolites in plants, which are compounds that have various biological and pharmacological activities. Therefore, in this study, the ajwain (Carum copticum L.) seeds were grown in MS medium containing different levels of FeONPs (0, 100, 200, and 400 mg l−1). After four weeks, the effects of FeONPs on growth, photosynthesis pigments, total phenolic, and anthocyanin content, activities of some antioxidant enzyme and secondary metabolites of ajwain) were investigated. The results showed that low levels of FeONPs (especially 200 mg l−1) increased fresh weight (231 %), total chlorophyll (49 %), total phenolics (259 %), anthocyanin content (110 %), as well as thymol (8 %) and γ-terpinene (16 %) content. Conversely, 400 mg l−1 FeONPs reduced root length (60 %) and fresh weight (64 %) was associated with a reduction in CAT activity, phenol (55 %), thymol (22 %), and γ-terpinene (18 %) content compared to ajwain treated with 200 mg l−1 FeONPs. This reduction was probably due to the increase in ROS caused by the low catalase enzyme activity and important essential oils compounds such as thymol and γ-terpinene. Thus, our results indicate that FeONPs at certain levels can be used as a new way for in vitro production of valuable essential oils and antioxidant compounds in ajwain.

Training set optimization is a feasible alternative for perennial orphan crop domestication and germplasm management: an Acrocomia aculeata example.

Orphan perennial native species are gaining importance as sustainability in agriculture becomes crucial to mitigate climate change. Nevertheless, issues related to the undomesticated status and lack of improved germplasm impede the evolution of formal agricultural initiatives. Acrocomia aculeata - a neotropical palm with potential for oil production - is an example. Breeding efforts can aid the species to reach its full potential and increase market competitiveness. Here, we present genomic information and training set optimization as alternatives to boost orphan perennial native species breeding using Acrocomia aculeata as an example. Furthermore, we compared three SNP calling methods and, for the first time, presented the prediction accuracies of three yield-related traits. We collected data for two years from 201 wild individuals. These trees were genotyped, and three references were used for SNP calling: the oil palm genome, de novo sequencing, and the A. aculeata transcriptome. The traits analyzed were fruit dry mass (FDM), pulp dry mass (PDM), and pulp oil content (OC). We compared the predictive ability of GBLUP and BayesB models in cross- and real validation procedures. Afterwards, we tested several optimization criteria regarding consistency and the ability to provide the optimized training set that yielded less risk in both targeted and untargeted scenarios. Using the oil palm genome as a reference and GBLUP models had better results for the genomic prediction of FDM, OC, and PDM (prediction accuracies of 0.46, 0.45, and 0.39, respectively). Using the criteria PEV, r-score and core collection methodology provides risk-averse decisions. Training set optimization is an alternative to improve decision-making while leveraging genomic information as a cost-saving tool to accelerate plant domestication and breeding. The optimized training set can be used as a reference for the characterization of native species populations, aiding in decisions involving germplasm collection and construction of breeding populations.

Tropical oils consumption and health: a scoping review to inform the development of guidelines in tropical regions

BackgroundTropical oils such as palm and coconut oils are renowned for their high saturated fat content and culinary versatility. However, their consumption has sparked debate regarding their health benefits and production concerns. The purpose of this review was to map existing evidence on the health benefits and challenges associated with the consumption of tropical oils.MethodThe recommendations for conducting a scoping review by Arksey and O’Malley were followed. PubMed, Dimensions AI, Central, JSTOR Google, Google Scholar, and ProQuest databases were searched for relevant papers. The predetermined keywords used were Consumption” AND “Tropical oil,” as well as “Health benefits” OR “Health challenges” AND “Tropical Countries.” Peer-reviewed and grey literature published in English were eligible for this review.ResultTropical oils, such as palm and coconut oils, provide health benefits including essential vitamins (A and E) that enhance ocular health, boost immunity, and support growth. They are also recognised for their role in managing high blood sugar, obesity, and cholesterol levels, while offering antioxidant and anti-inflammatory properties. These oils have wound-healing abilities and are commonly used in infant nutrition and traditional cooking. Nevertheless, prolonged and repeated use of tropical oils to high temperature can degrade vitamin E, whereas excessive intake may result in overdose. Health concerns include oxidative risks, diabetes, cancer, coronary heart disease, high blood pressure, and acrylamide formation due to production challenges excessive consumption. Additional issues include obesity, suboptimal oil production, misconceptions, regulatory obstacles, and preferences for alternative fats.ConclusionThis review suggest that tropical oils provide essential health benefits, including vitamins and antioxidant properties, but pose significant health risks and production challenges, particularly when exposed to high temperatures and through excessive intake. Guidelines on the consumption of tropical oils in the tropical regions are necessary to regulate their consumption.

A novel grey seasonal model with time power for energy prediction

The fluctuation of seasonal time series has attracted considerable attention. However, the complexity of socio-economic development and the variability of influencing factors make accurate predictions of seasonal time series more difficult. A new discrete grey seasonal model, namely DGSTPM(1,1), is established, which employs the time power term based on the cultural algorithm to effectively deal with the time sequences characterized by nonlinear tendency and periodic fluctuations. Firstly, the operating mechanism of the DGSTPM(1,1) model is expounded by combining the time power item with the traditional grey seasonal model to enhance the forecasting capability. Then, the optimal time power index of the model can be determined by incorporating the cultural algorithm. Subsequently, several properties are thoroughly discussed to illustrate the superiority and uniformity of the new model. Finally, two energy-related cases with different data features and sample sizes are applied to identify the efficacy and robustness of the DGSTPM(1,1) model, referring to monthly crude oil production in the United States and quarterly coke production in China. Based on the various error criteria, SPA and DM tests, the results indicate that the DGSTPM(1,1) outperforms its competitors both in simulation and prediction phases, including DGSTM(1,1), SGM(1,1), SDTGM, FTGM, SARIMA, LSSVM, BPNN, and LSTM models. Meanwhile, the new model can effectively address seasonal time series with nonlinear characteristics owing to its dynamic time power item with the support of the cultural algorithm.

Research for the Enhanced Oil Recovery Mechanism of Heavy Oil after Composite Huff and Puff Assisted by Edge-Bottom Water Displacement

Abstract In the late stage of exploiting heavy oil reservoirs with edge-bottom water, we are faced with problems such as high crude oil viscosity, channeling of bottom water, and rapid rise in water cut. To clarify the synergistic effect of N2, CO2, N2 foam, and viscosity reducer in water control and oil increase, and solve the problem of edge-bottom water rushing into production wells, one-dimensional sand-pack huff and puff experiments were carried out. First, the N2 foam huff and puff experiment evaluated the effect of N2 foam on controlling bottom water. Then the viscosity reducer assisted CO2 huff and puff experiment analyzed the synergistic viscosity reduction ability between the two to mobilize the remaining heavy oil. Next, the N2 foam-viscosity reducer-CO2 huff and puff experiment clarified the synergistic effect between the three. Finally, the N2 foam-viscosity reducer-CO2-N2 huff and puff experiment solved the problem of insufficient reservoir energy based on synergistic precipitation and oil increase. Experimental results show that N2 foam-viscosity reducer-CO2-N2 huff and puff is the optimal water control and oil increase solution. This solution can significantly reduce water production and increase oil production. In the one-dimensional sand-pack experiment, this technical solution reduced the water content by 68% and increased the recovery rate by 16.09%. The research results provide a reference for the development of exploitation technology schemes for similar edge-bottom water heavy oil reservoirs after entering high water cut.

Integrated geological quality evaluation using advanced wireline logs and core data: a case study on high clay shale oil reservoir in China

Abstract In the unconventional energy sector, shale oil is increasingly recognized as a crucial supplement to production. In recent years, China has made significant advancements in the development of shale oil. A unique type of pure shale reservoir in the Songliao basin, distinct from established shale oil reservoirs worldwide, has emerged as a focal point for exploration and research endeavors. This kind of shale exhibits enhanced heterogeneity, high clay content, intricate rock electricity relationship, posing significant challenges to formation evaluation. This study introduces conversion coefficients for the elements and minerals, a decision tree model, a variable T2 cutoff value method, and 2D NMR cluster analysis, all based on the integration of microimaging, spectroscopy, and 2D NMR logging. These novel approaches facilitate a comprehensive geological quality evaluation of key parameters, including mineral composition, lithology, effective porosity, total organic carbon content, fluid composition, and saturation characteristics within pure shale formations from the Songliao Basin. The established petrophysical model has been validated by core analysis data and successfully applied in exploration wells. Through systematic petrophysical analysis, the optimal landing point for horizontal wells was identified based on the identification of the best reservoir quality interval with high movable oil and oil saturation. The subsequent drilling of horizontal wells demonstrated the reliability of petrophysical evaluation in terms of oil production. This integrated evaluation method for pure shale holds reference significance for similar shale reservoirs in other blocks in the future.

In-situ upgrading of Egyptian heavy crude oil using matrix polymer carboxyl methyl cellulose/silicate graphene oxide nanocomposites

This study delves into catalytic aquathermolysis to enhance the economic viability of heavy oil production by in-situ upgrading technique. It is known that introducing nanocatalysts would promote the aquathermolysis reaction. Therefore, in this study, the effect of matrix polymer carboxyl methyl cellulose/silicate graphene oxide nanocomposites (CSG1 and CSG2) in the catalytic aquathermolysis of Egyptian heavy crude oil was studied. Characterization techniques including Fourier-transform infrared (FTIR), X-ray diffraction (XRD), Dynamic light scattering (DLS), Brunauer–Emmett–Teller (BET) surface area analysis, Scanning electron microscopy (SEM), and thermogravimetric analysis (TGA) were used to evaluate the structure of the synthesized nanocomposites. Results reveal CSG2 has higher crystallinity and superior dispersion compared to CSG1, and both exhibited a good stability in aqueous suspensions. CSG2 enriched with graphene oxide, demonstrates superior thermal stability, suitable for high-temperature applications such as catalytic aquathermolysis process. Single factor and orthogonal tests were used to assess the catalytic aquathermolysis performance of the prepared nanoparticles. The obtained results revealed that the optimum conditions to use CSG1 and CSG2 are 40% water concentration, 225 °C temperature, and 0.5 wt% catalyst percentage. Where, CSG2 showed better viscosity reduction (82%) compared to CSG1 (62%), highlighting its superior performance in reducing the viscosity of heavy oil. Numerical results from SARA analysis, gas chromatography, and rheological testing confirmed the catalytic aquathermolysis's efficacy in targeting asphaltene macromolecules and producing lighter hydrocarbon fractions.