Petroleum Research最新文献

{"title":"Sedimentary characteristics and geological significance of a mixed-process delta for petroleum exploration in the Zhuhai formation of the Baiyun Depression, Pearl River Mouth Basin, China","authors":"Xiaojun Xie ,&nbsp;Wu Tang ,&nbsp;Shangfeng Zhang ,&nbsp;Rui Zhu ,&nbsp;Dongxu Fan ,&nbsp;Ran Li","doi":"10.1016/j.ptlrs.2024.06.004","DOIUrl":"10.1016/j.ptlrs.2024.06.004","url":null,"abstract":"<div><div>The Zhuhai Formation in the Baiyun Depression of the Pearl River Mouth Basin in the northern South China Sea is a marine delta influenced by multiple hydrodynamic forces, including rivers, waves, and tides, resulting in a mixed-process delta. As a result of the combined effects of these forces, the distribution patterns and reservoir structures in the sandstone formations of the Zhuhai Formation are extremely complex. This paper provides a detailed description of the coring section of the Zhuhai Formation drilled in the Baiyun Depression, focusing on the lithology, sedimentary structure, special containers, and depositional dynamics of the coring section. It also summarizes the characteristics of a hybrid power delta controlled by rivers, waves, and tides, and explores the geological significance of this mixed-process delta for oil and gas exploration. The study reveals that sedimentation controlled by rivers primarily consists of medium-to-fine sandstones with interbedded cross-bedding and parallel bedding. Scour-fill structures and a bell or box-shaped natural gamma ray logging curve (GR) are also observed. Seismic reflection exhibits strong amplitude and high continuity. Wave-controlled sedimentation, on the other hand, predominantly consists of silt and fine sandstones with scouring, wave-formed cross-bedding, abundant bioturbation, and a serrated and funnel-shaped GR curve. Seismic reflection shows medium amplitude and high continuity. Tidally-controlled deposits are characterized by thin interbeds of mudstone, siltstone, and fine sandstone, as well as vein laminations, undulating composite laminations, lenticular laminations, and biclastic layers. The GR curves for tidally-controlled deposits are sharp or jagged with funnel shapes, and seismic reflections exhibit medium amplitude and continuity. The hydrodynamic features controlling sedimentation during the depositional period of the Zhuhai Formation in the Baiyun Depression exhibit evident zonation on a planar scale, influenced by sedimentary paleogeography and sea-level changes. River control is predominant in the northern Zhuhai Formation, with local wave influence and minimal tidal influence. In the southern part, tidal action becomes increasingly important. In terms of reservoir properties, wave-controlled reservoirs display significantly better porosity and permeability compared to tidally-controlled and river-controlled reservoirs. Tidally-controlled reservoirs exhibit high heterogeneity with a wide range of porosity and permeability values. The varying influences of different hydrodynamic drivers in different locations have led to significant variations in the size, morphology, and physical properties of sand bodies within the marine delta sediments of the Zhuhai Formation in the Baiyun Depression. Thus, the type and intensity of sedimentary hydrodynamics become the primary controlling factors for the development of high-quality reservoirs.</div></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"9 4","pages":"Pages 599-609"},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141396976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review on oilfield produced water and its treatment technologies","authors":"Amarjit Rajbongshi ,&nbsp;Subrata Borgohain Gogoi","doi":"10.1016/j.ptlrs.2024.06.003","DOIUrl":"10.1016/j.ptlrs.2024.06.003","url":null,"abstract":"<div><div>Owing to the soaring urge to meet the demand for oil and gas on different frontiers, its exploration all over the world is of paramount importance. Exploration and production of oil calls for handling a huge volume of associated water, produced along with it, referred to as Oilfield Produced Water (OFPW). OFPW is considered a potential threat to the environment due to the presence of toxic constituents such as dissolved and dispersed oil compounds, dissolved formation minerals, production chemical compounds, production solids (formation, corrosion, scale, bacteria, waxes, and asphaltenes), dissolved gases. This review is intended to provide information on OFPW, its constituents, impact, and treatment technologies of OFPW from various oilfields across the world. It presents a meticulous analysis of the scope of reusing OFPW instead of freshwater for various processes such as well drilling and completion, re-injection to the reservoir for pressure maintenance, and water flooding process for secondary recovery of crude oil. The reuse of OFPW can reduce the demand for fresh water and turn the wastewater into useable water resources after proper treatment. The paper provides rigorous information on the importance of developing an eco-friendly treatment process for the proper reuse and management of OFPW.</div></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"9 4","pages":"Pages 640-656"},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141404241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of triton-assisted coconut shell derived graphene nanoplatelets in water-based drilling fluid lubricity and shale inhibition application","authors":"Muftahu N. Yahya ,&nbsp;M.N.A.M. Norddin ,&nbsp;Issham Ismail ,&nbsp;A.A.A. Rasol ,&nbsp;N. Salahudeen ,&nbsp;Jeffrey O. Oseh ,&nbsp;M. Muhammad ,&nbsp;M. Shahid ,&nbsp;Shaziera B. Omar","doi":"10.1016/j.ptlrs.2024.06.002","DOIUrl":"10.1016/j.ptlrs.2024.06.002","url":null,"abstract":"<div><div>Insufficient hole cleaning, cutting suspension, clay swelling, and filtrate invasion of the formation might result from inadequate drilling mud properties. For effective drilling and wellbore stability, water-based mud (WBM) rheology, lubricity, filtration, and shale inhibition must be optimized and controlled. WBMs react with clays and cause time-dependent borehole issues, which is their principal drawback. Moreover, prolonged exposure destroys certain WBM components, resulting in minimal mud properties. These indicate the need for multifunctional additives to improve WBMs. Thus, this study developed WBM systems employing graphene nanoplatelets (GNPs) and locally acquired discarded coconut shells to overcome severe drilling challenges. By adding triton-X100 to coconut shell-based graphene (GN-CS), a greater dispersion of modified graphene (GN-TX) particles was produced. Characterization, rheology, lubricity, inhibition, and filtration tests were performed on these GN-CS and GN-TX at concentrations of 0.125, 0.25, 0.375, and 0.50 wt%. Furthermore, biotoxicity, biodegradability, and heavy metal content experiments were performed to study the environmental impact of GN-CS and GN-TX. The results showed that GN-TX had good thermal resistance up to 300 °C with only a 10% loss in weight. Both EDX and FTIR tests showed that the epoxy, carboxyl, and hydroxyl groups are in the GNP-based materials' basal plane. The GN-CS and GN-TX had better fluid properties, including better lubricity, rheology, filtration, and inhibition over the base mud, and the optimal rheological model of the drilling muds was the Herschel Buckley model. The GN-TX (modified) decreased the fluid loss to 20.6–14.3 mL from 24.6 mL at 353 K, whereas the GN-CS (unmodified) reduced it to 21.3–16.7 mL. GN-TX and GN-CS decreased the coefficient of friction of WBM from 0.47 to 0.55 to 0.25–0.41 and 0.33–0.44, respectively, from 298 to 353 K. In addition, 0.50 wt% of GN-CS and GN-TX reduced the shale pellet swelling height to 5.4% and 5.6%, respectively, from 8.8%. Moreover, the EC₅₀ values for GN-CS and GN-TX were about 54,000 mg/L and the BOD/COD ratio was about 47%. These results show that the GNP-based products are safe and biodegradable. The GNP-based materials have promising prospects for drilling in environmentally sensitive formations.</div></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"9 4","pages":"Pages 620-639"},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141410266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chemometric analysis on concentrations and ratios of terpanes and steranes and implications for oils from the cratonic region of the Tarim Basin, NW China","authors":"Yuanyuan Bian ,&nbsp;Chenxi Zhou ,&nbsp;Haizu Zhang ,&nbsp;Zhongyao Xiao ,&nbsp;Zhaowen Zhan ,&nbsp;Shuang Yu ,&nbsp;Changchun Pan","doi":"10.1016/j.ptlrs.2024.06.001","DOIUrl":"10.1016/j.ptlrs.2024.06.001","url":null,"abstract":"<div><div>More than 2 × 10⁹ tonnes of proved oils have been found in the cratonic region of the Tarim Basin. The source rocks for these oils remain unresolved although the source rocks are marine facies within the Cambrian and Ordovician strata with total thickness over 5 km. So far, there is no systematic classification of these oils on the basis of source facies. In this study, a practical approach was presented to select effective and sensitive biomarker parameters for source facies and maturity assessments for the studied oils on the basis of biomarker classification by hierarchical cluster analysis (HCA). Twenty-one terpanes and steranes in oils from both the Tabei (Northern Tarim) and Tazhong (Central Tarim) uplifts were classified into three groups using HCA on the basis of terpane and sterane concentrations. The result of biomarker grouping mainly reflects the differences in thermal stabilities among biomarkers for the 45 Tabei oils, providing a general thermal stability sequence for terpanes and steranes that helps the selection of effective maturity parameters. However, biomarker grouping suggests that both source facies and thermal stability have major influences on relative biomarker concentrations for the 75 Tazhong oils. The Tabei oils are mainly derived from a single source with relatively homogeneous facies while the Tazhong oils are derived from multiple sources or a single source with more heterogeneous facies. Based on the HCA results, twelve terpane and sterane ratios were selected as source facies parameters for the Tabei and Tazhong oils. These studied oils were consequently classified into four families by HCA and principle component analysis (PCA) integrating the twelve selected facies parameters of terpanes and steranes along with Pr/<em>n</em>-C₁₇ and Ph/<em>n</em>-C₁₈ ratios. Family 1 and 2 oils are mainly in the Tabei uplift while Family 3 and 4 oils are almost in the Tazhong uplift. Family 1 and 2 oils are derived from source rocks located at the northern, central and southern areas of the Northern Depression and the Tabei Uplift with marine mudstone facies. Family 3 and 4 oils are derived from source rocks located mainly at the southern area of the Northern Depression and the Tazhong Uplift with carbonate and evaporite facies. This study provides a practical approach to trace oil origins for oil and condensate reservoirs in the Tarim Basin and elsewhere.</div></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"9 4","pages":"Pages 565-585"},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141410793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A multi-mechanistic approach to the oil recovery study of a family of amphiphilic polysaccharides","authors":"Funsho Afolabi ,&nbsp;Syed M. Mahmood ,&nbsp;Lunech Mario ,&nbsp;Nur Asyraf Md Akhir ,&nbsp;Bennett Tackie-Otoo ,&nbsp;Hamid Sharifigaliuk","doi":"10.1016/j.ptlrs.2023.12.001","DOIUrl":"https://doi.org/10.1016/j.ptlrs.2023.12.001","url":null,"abstract":"<div><p>Chemical enhanced oil recovery (cEOR) remains one of the most potent tertiary recovery techniques. However, it is expensive and rarely environmentally friendly. Bio-based amphiphilic polymers have been suggested as an alternative to eradicating the challenges of conventional cEOR because of cost-effectiveness, and sustainability. Unfortunately, few in-depth studies exist in the literature to investigate the prospects of these materials. A new family of amphiphilic polysaccharides was synthesized by hydrophobic modification of cellulose sulphate, and the EOR functionalities were tested. The novel biopolymers exhibited the ability to alter rock wetting properties. In terms of recovery, one of the variants of the synthesized bio amphiphilic polymer (D-I) was able to reduce residual oil saturation to 12% at harsh conditions of 60,000 ppm salinity at 75 °C. Micromodel visual analysis revealed that the performance of the novel materials was due to the combination of mobility control, IFT lowering and emulsification, wettability alteration, and viscoelasticity. With a performance commensurate to that of a commercial hydrophobically modified polymer, it can be said that the novel amphiphilic polysaccharides can stand as a viable cEOR agent for oilfield applications.</p></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"9 2","pages":"Pages 238-249"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096249523000893/pdfft?md5=caa216e66c07749c33c7e8eb3e6adbe0&pid=1-s2.0-S2096249523000893-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141423105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of carbonate sedimentary facies from well logs with machine learning","authors":"Xianmu Hou ,&nbsp;Peiqing Lian ,&nbsp;Jiuyu Zhao ,&nbsp;Yun Zai ,&nbsp;Weiyao Zhu ,&nbsp;Fuyong Wang","doi":"10.1016/j.ptlrs.2024.01.007","DOIUrl":"10.1016/j.ptlrs.2024.01.007","url":null,"abstract":"<div><p>Sedimentary facies identification is critical for carbonate oil and gas reservoir development. The traditional method of sedimentary facies identification not only be affected by the engineer's experience but also takes a long time. Identifying carbonate sedimentary facies based on machine learning is the trend of future development and has the advantages of short time consuming and reliable results without engineers' subjective influence. Although many references reported the application of machine learning to identify lithofacies, but identifying sedimentary facies of carbonate reservoirs is much more challenging due to the complex sedimentary environment and tectonic movement. This paper compares the performance of the carbonate sedimentary facies identification using four different machine learning models, and the optimal machine learning with the highest prediction accuracy is recommended. First, the carbonate sedimentary facies are classified into the lagoon, shallow sea, shoal, fore-shoal, and inter-shoal five tags based on the well loggings. Then, five well log curves including spectral gamma ray (SGR), uranium-free gamma ray (CGR), photoelectric absorption cross-section index (PE), true formation resistivity (RT), shallow lateral resistivity (RS) are used as the input, and the manual identified carbonate sedimentary facies are used as the output of the machine learning model. The performance of four different machine learning algorithms, including support vector machine (SVM), deep neural network (<span>DNN</span>), long short-term memory (<span>LSTM</span>) network, and random forest (RF) are compared. The other two wells are used for model validation. The research results show that the RF method has the highest accuracy of sedimentary facies prediction, and the average prediction accuracy is 78.81%; the average accuracy of sedimentary facies prediction using SVM is 77.93%. The sedimentary facies predictions using DNN and LSTM are less satisfying compared with RF and SVM, and the average accuracy is 69.94% and 73.05%, respectively. The predicted carbonate sedimentary facies by LSTM are more continuous compared with other machine learning models. This study is helpful for identifying compelx sedimentary facies of carbonate reservoirs from well logs.</p></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"9 2","pages":"Pages 165-175"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096249524000073/pdfft?md5=4ecc1f769bf586c8fbae3c73c4a35aa9&pid=1-s2.0-S2096249524000073-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139538637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the potential of drill cuttings for reservoir characterization: A case study from the Volga-Ural basin, Russia","authors":"Ibrahem Yousef,&nbsp;V.P. Morozov","doi":"10.1016/j.ptlrs.2024.01.012","DOIUrl":"10.1016/j.ptlrs.2024.01.012","url":null,"abstract":"<div><p>The research objectives are to assess the possibility of using drill cutting analysis to obtain information about the mineralogical and geochemical properties of the reservoir rocks. Drill cutting samples were collected from a vertical well that penetrated the Domanik sediments (Semiluksk Formation) in one of the oil fields in the Volga-Ural petroleum province. Thin sections from drill cuttings were examined using an optical polarizing microscope (Axio Imager A2). X-ray diffraction (XRD) analyses were performed using a Brucker D2 Phaser X-ray powder diffractometer. Thermophysical properties were studied using an STA 449 F3 Jupiter instrument. The pyrolytic studies were performed using the Rock-Eval method. Visual inspection showed that the studied sediments are alternations of carbonates and siliceous-carbonate rocks. Thin section examinations revealed that the carbonates are mainly limestone (mudstone and wackestone) and are characterized by a dense texture and up to 30 % organic residues. The siliceous-carbonate rocks are dominated by siliceous mudstones and are characterized by dark colours, layered structure, and an enrichment in organic matter. XRD analyses showed that the carbonate rocks are mainly composed of calcite, dolomite, quartz, feldspar, and mica, which are minor components. The siliceous-carbonate rocks are dominated by quartz, followed by calcite, although they also contain feldspars, mica, dolomite, and pyrite as impurities. According to the simultaneous thermal analysis, the average total hydrocarbon in the carbonate and siliceous-carbonate rocks is 13.6 % (for the core samples) and 11.5 % (for the drill cutting samples). The content of heavy hydrocarbons in the rocks is higher than the content of light hydrocarbons, indicating the immature nature of organic matter. Kerogen is found sporadically in siliceous-carbonate rocks. According to the pyrolytic studies, average S1 is 4.4 mg/g and average S2 is 19.8 mg/g (for the core samples); average S1 is 2.1 mg/g and average S2 is 17.8 mg/g (for the drill cutting samples), which indicated that the studied sediments have very good to excellent generation potential. The average <em>T</em>_<em>max</em> of 425.7 °C (for the drill cutting samples) and 427.9 °C (for the core samples) indicate immature organic matter that generated only heavy oils. Comparing the results of the analysed drill cutting samples with the results of the analysed core analysis from the same reservoir interval in the neighbouring wells showed a good correlation, which proves that this technique is a valid tool that provides an alternative, cost-effective method to determine the rock's characteristics from drill cuttings.</p></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"9 2","pages":"Pages 193-205"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096249524000127/pdfft?md5=d708ca679302a7496309c9e1204ac5e7&pid=1-s2.0-S2096249524000127-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140520919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of bismuth-based solutions for well plugging and abandonment: A review","authors":"Lewaa Hmadeh,&nbsp;Marcelo Anunciação Jaculli,&nbsp;Behzad Elahifar,&nbsp;Sigbjørn Sangesland","doi":"10.1016/j.ptlrs.2024.01.003","DOIUrl":"10.1016/j.ptlrs.2024.01.003","url":null,"abstract":"<div><p>Plugging and abandonment (P&amp;A) is a crucial step of the well life cycle. Regardless of how long one stretches the productive life of a well, P&amp;A operations will have to be carried out eventually. The current panorama of our industry includes many wells to be plugged and abandoned, with steep requirements to abide by both regulations and societal pressure. In this context, we must guarantee that no leakage occurs with an eternal perspective in mind. Cement has been the prime material for this task, but recent studies have indicated the potential of degradation over time – especially in corrosive environments – and the creation of leaking paths due to its shrinkage. This has opened up a path toward the usage of alternative materials. One of the emerging candidates is bismuth, a metal with the unique characteristic of expanding when solidified. Such a trait could improve the overall sealability of wellbores and especially during P&amp;A. This article discusses the current status of bismuth sealing technologies, introducing the basics of bismuth, the ongoing efforts to qualify it as a barrier material, its potential applications, and the challenges that still need to be overcome. The latest research indicates promising results in terms of its usage as a barrier element.</p></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"9 2","pages":"Pages 250-264"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096249524000036/pdfft?md5=2f8b22bcf397921390078ff8c7456667&pid=1-s2.0-S2096249524000036-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139636880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrosion testing of X52 and X80 steels immersed in stimulated emulsions using a real petroleum sample","authors":"L.M. Quej-Ake,&nbsp;J.L. Alamilla,&nbsp;A. Contreras","doi":"10.1016/j.ptlrs.2024.01.002","DOIUrl":"10.1016/j.ptlrs.2024.01.002","url":null,"abstract":"<div><p>The aim of this study is to evaluate the internal corrosion process on X52 and X80 steels/real petroleum interfaces containing condensed hydrocarbon plus oilfield-produced water, which were subjected to stimulated emulsions using 50/50 vol ratio mixtures at 45 °C, different hydrodynamic conditions, 1 h, and 24 h. A washing process by using deionized water was proposed to simulate and identify the corrosiveness of the hydrocarbon phase after 24 h of exposure time. The characterization by electrochemical impedance spectroscopy and the monitoring of the polarization curves indicated that X80 steel/oilfield-produced water interfaces were more susceptible to corrosion than X52 steel exposed to oilfield-produced water. The combined speed rotation of 600 rpm using a magnetic stirrer + 600 rpm using a rotating disk electrode decreased the corrosion rate on X52 steel. The stimulated emulsions made of hydrocarbon + oilfield-produced water and hydrocarbon + deionized water at 24 h increased the corrosion rate on X80 steel (0.34 mm/year and 0.43 mm/year, respectively), promoting the formation of erosion and pitting corrosion. These types of corrosion depended mainly on the physicochemical properties of the hydrocarbon, oilfield-produced water, exposure times, and hydrodynamic systems in which the hydrocarbon was studied.</p></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"9 2","pages":"Pages 304-316"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096249524000024/pdfft?md5=50dab8f7d69571753a875691db537421&pid=1-s2.0-S2096249524000024-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139540798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting density log from well log using machine learning techniques and heuristic optimization algorithm: A comparative study","authors":"Mehdi Rahmati ,&nbsp;Ghasem Zargar ,&nbsp;Abbas Ayatizadeh Tanha","doi":"10.1016/j.ptlrs.2024.01.008","DOIUrl":"10.1016/j.ptlrs.2024.01.008","url":null,"abstract":"<div><p>In the petroleum industry, the analysis of petrophysical parameters is critical for efficient reservoir management, production optimization, development strategies, and accurate hydrocarbon reserve estimations. Over recent years, the integration of machine learning methodologies has revolutionized the field, addressing challenges in geology, geophysics, and petroleum engineering, even when confronted with limited or imperfect data. This study focuses on the prediction of density logs, a pivotal factor in evaluating reservoir hydrocarbon volumes. It is important to note that during well logging operations, log data for specific depths of interest may be missing or incorrect, presenting a significant challenge. To tackle this issue, we employed the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANN) in combination with advanced optimization algorithms, including Particle Swarm Optimization (PSO), Imperialist Competitive Algorithms (ICA), and Genetic Algorithms (GA). These methods exhibit promising performance in predicting density logs from gamma-ray, neutron, sonic, and photoelectric log data. Remarkably, our results highlight that the Genetic Algorithms-based Artificial Neural Network (GA-ANN) approach outperforms all other methods, achieving an impressive Mean Squared Error (MSE) of 0.0013. In comparison, ANFIS records an MSE of 0.0015, ICA-ANN 0.0090, PSO-ANN 0.0093, and ANN 0.0183.</p></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"9 2","pages":"Pages 176-192"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096249524000085/pdfft?md5=9c5236924d89719aebc109365066ee17&pid=1-s2.0-S2096249524000085-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140516300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}