Day 1 Tue, October 22, 2019最新文献

{"title":"Complex Approach for Gas Lift Wells Optimization for Orenburgskoe Field","authors":"Eugene Kapusta, K. Rymarenko, M. Nukhaev, S. Grishenko, Galymzhan Aitkaliev, D. Minin, V. Kabanov, Denis Galkin, T. Karamysheva, V. Ulyanov, N. Dadakin","doi":"10.2118/196818-ms","DOIUrl":"https://doi.org/10.2118/196818-ms","url":null,"abstract":"\u0000 At the moment in Russia, the gas-lift method of operation is becoming popular again not only because of the significant reduction in operating costs, ease of operation, but because of the involvement in the development of a large number of assets with oil rims. This paper describes an integrated approach to optimizing the operation of wells in the Orenburg oil and gas condensate field, which is characterized by the largest number of wells in Russia that are operated by gas lift. The paper describes traditional approaches to the gaslift well testing as well as a new approach to improve operational efficiency.","PeriodicalId":143392,"journal":{"name":"Day 1 Tue, October 22, 2019","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128487963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of an Approach for the Numerical Analysis of Well Interference","authors":"S. Bukhmastova, R. Fakhreeva, Y. Pityuk, R. Akhmerov, D. Efimov, O. Nadezhdin","doi":"10.2118/196848-ms","DOIUrl":"https://doi.org/10.2118/196848-ms","url":null,"abstract":"\u0000 Information about the interwell space allows one to solve a number of key production problems such as planning of geological and technical measures and enhancement of operating efficiency of wells. Due to the fact that this information is most often recovered from the interpretation models, one of the ways to obtain correct information is the analysis of well interference. It helps to obtain knowledge about the state of the reservoir, the degree of its heterogeneity and the presence of cracks and fractures.\u0000 The aim of the study is development of a comprehensive approach for the analysis of reservoir connectivity by identifying well interference based on the mutual accounting of pressure and flow-rate data of well field. In order to solve this problem, we developed programing modules based on the methods of Multivariate Linear Regression (MLR) and Capacity-Resistance Model Injector-Producer (CRMIP). The main advantages of these algorithms are their low cost, high speed of operation, and the absence of the need for knowledge about the location of wells in the field and the physical properties of the formation. The MLR method is based on the pressure analysis with the use of the multivariate linear regression equation. The outputs are the weighting coefficients of well interference. To solve the problem using the CRMIP method we require a history of injection and production, bottomhole pressure of the production wells. The CRMIP takes into account the equation of material balance. On the basis of these data and the solution of the optimization problem we determine the coefficients of well interference, time delay in system response, and productivity coefficients.\u0000 The programing modules were tested on various synthetic data in order to quantify the coefficients of well interference and to verify the predictive ability of the models. Good agreement of numerical results with baseline data is obtained. The analysis of the results of numerical simulation indicated that all the interference coefficients are defined correctly.","PeriodicalId":143392,"journal":{"name":"Day 1 Tue, October 22, 2019","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127349842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of Different Types Flowmeters for Gas Lift Metering on Orenburgskoe Field","authors":"K. Rymarenko, M. Nukhaev, S. Grishenko, N. Chernysh, S. Titov, A. Zaycev, N. Dadakin, V. V. Ulyanov","doi":"10.2118/196824-ms","DOIUrl":"https://doi.org/10.2118/196824-ms","url":null,"abstract":"\u0000 Gas or liquid flow control is one of the most important technical tasks in the oil and gas industry. The choice of a particular device most often occurs on the basis of the established practice of application in a particular company. This paper presents the experience of Gazpromneft-Orenburg in the use of overhead and stationary flow meters of various types, including ultrasonic and restriction devices for measuring gas-lift gas in the Orenburg oil and gas condensate field.","PeriodicalId":143392,"journal":{"name":"Day 1 Tue, October 22, 2019","volume":"12 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131590234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Practical Application of High-Resolution Reservoir Simulation and High-Performance Computing for Accurate Modeling of Low Permeability Gas Condensate Reservoirs Production","authors":"R. Sharafutdinov, V. Tyurin, D. Fateev, S. Skvortsov, Y. Dolgikh, D. Tokarev, Dmitry Shakhov, A. Voznyuk, Larisa Pyatkevich, E. Kovaleva","doi":"10.2118/196916-ms","DOIUrl":"https://doi.org/10.2118/196916-ms","url":null,"abstract":"\u0000 One of the main aspects that is worth paying attention to when planning the development of gas-condensate (GC) fields is accounting for and reproducing gas-liquid phase transitions that affect the flow of hydrocarbons (HC) in the reservoir as well as gas and condensate production indicators during the entire life cycle of the field. Undoubtedly, this effect will be more significant for cases with a complex gas component composition, high condensate content, as well as under conditions of low reservoir formation permeability and a high degree of areal and vertical heterogeneity. Compositional hydrodynamic modeling is a comprehensive tool for assessing hydrocarbon production capabilities, taking into account the phase behavior for GC field. The purpose of this work is to compare the various methods of improving the accuracy of numerical simulations and the reliability of the hydrodynamic modeling results for this type of reservoirs.\u0000 Using a high-resolution hydrodynamic simulator and a high-performance cluster system, multivariate simulations were performed to evaluate the effect of various parameters and options on the results of numerical simulations. The simulations were carried out using a compositional model, which is an analogue of a gas-condensate fields in Western Siberia within Yamalo-Nenetsky Autonomous Okrug (YNAO), based on geology, PVT and core, production history and well test data for vertical and subhorizontal wells, accounting for the presence of hydraulic fracturing. The work started with a detailed study of the challenge while the GC systems modeling on local sectors with further transition to a larger scale models using the results obtained on the previous step, taking into account their cross-validation.\u0000 Based on the results of the work, several important decisions (observations) were made, allowing determining the potential limits and the technical capability of modeling the GC systems with the required accuracy of phase transitions. In addition, the degree of influence if the numerical grid resolution and detalization of the PVT model (up to 50 components inclusive) on the gas and oil production and the pressure behavior was estimated. The simulation run time with various numerical schemes were also considered as factors affecting the simulation results on the sector and full-scale models. The analysis carried out and the results obtained can be further used by engineers dealing with GC field development as a guideline for choosing the modeling method depending on the complexity of the task and available computational resources.","PeriodicalId":143392,"journal":{"name":"Day 1 Tue, October 22, 2019","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122934351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Borehole Acoustic Reflection Survey in Horizontal Wells: High Resolution Reservoir Structure to Guide Properties Distribution","authors":"Y. Karpekin, S. Orlova, R. Tukhtaev, Alexey Ovchinnikov, V. Kuntsevich","doi":"10.2118/196958-ms","DOIUrl":"https://doi.org/10.2118/196958-ms","url":null,"abstract":"\u0000 The article discusses the method of borehole acoustics reflection survey for detecting the presence and reconstructing the position of various reflecting surfaces, such as of large fractures, faults, bed-boundaries, in the near-well space at a distance up to 30m or more. The measurement principles, data processing, visualization and interpretation workflow developed by us based on the best published practices and supplemented by our solutions that significantly improve the quality and usability of the images are explained. A study of fractured zones identification and characterization in three horizontal wells based on the electrical microimager and the reflected acoustic survey is presented. Possibility of imaging the bed-boundaries of the host layers above and below the wellbore and specifying their position relative to the well's trajectory is demonstrated. Confinement of rocks with different reservoir quality within certain sub-layers of the target productive strata, identified with acoustic reflected survey, brings possibility to populate these properties more accurately in a refined structural model.","PeriodicalId":143392,"journal":{"name":"Day 1 Tue, October 22, 2019","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124876812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Compositions of Anionic and Non-Ionic Surfactants within a Hybrid EOR Technology for Unconventional Hydrocarbon Reservoirs","authors":"P. Afanasev, A. Scerbacova, A. Tsyshkova, E. Mukhina, P. Grishin, V. Grishaev, A. Cheremisin, I. Koltsov, Ekaterina Dvoretskaya, A. Kasyanenko, V. Demo, K. Prochukhan, A. Cheremisin","doi":"10.2118/196759-ms","DOIUrl":"https://doi.org/10.2118/196759-ms","url":null,"abstract":"\u0000 It is well known that the development of unconventional reserves is quite complicated due to the poor reservoir porosity and permeability. The use of horizontal wells with multi-stage hydraulic fracturing remains one of the promising methods in use today for the development of such reserves. Subsequently, tertiary recovery methods popularly known as enhanced oil recovery (EOR) can then be carried out. In this paper, the compositions of anionic and non-ionic surfactants, potentially suitable for use in unconventional hydrocarbon deposits as EOR agents were investigated (on the example of one of the fields of Bazhenov formation). Also, attention was devoted to the assessment of the feasibility of co-injecting the surfactant solutions with a thermal agent (subcritical water) in a hybrid thermo-chemical EOR process.\u0000 During the course of the study, 35 samples of industrial surfactants (individual and blends) were investigated. The compatibility of the surfactants with brine water, their stability under reservoir conditions (T>100 °C, P=25 MPa) for more than 14 days, and the effectiveness of the surfactants in reducing the interfacial tension (IFT) at the oil-brine boundary were the key factors in choosing the most appropriate compositions for use in the hybrid EOR. The ability of surfactants to decrease the IFT was investigated using a spinning drop tensiometer while the wettability alteration effect was estimated using a drop shape analyzer. Filtration experiment on oil-saturated core sample and evaluation of surfactant adsorption on rock surface were carried out with the best compositions.\u0000 The results of the study show that the colloidal systems, represented by mixtures of anionic and non-ionic surfactants, have the best performance. The main components of these surfactant compositions are sodium salts of olefin sulfonates, derivatives of sulfonic acids C15-C20, and ethoxylated alcohols C6-C12. The results of measurements imply that certain compositions alter the initial rock wettability to become more water-wet and reduce the IFT between oil and water to a value of 0.051 mN/m. The adsorption of surfactant molecules on the rock was estimated to be 4 g/kg of rock, and the ultimate oil displacement rate increased due to surfactant injection from 8 % obtained during water flooding to 40.5 %. The possibility of using surfactants within the hybrid EOR technology was proven because the best surfactant mixture showed thermal stability at temperatures above 250 °C.\u0000 Thus, we can conclude about the possibility of the use of some surfactant mixtures for the development of unconventional oil fields. Also, it is possible to combine the injection of surfactant solutions with the injection of thermal fluid, leading to the generation of synthetic oil in situ, thereby improving the reservoir properties of the rock and recovery of additional oil due to the effect of surfactants. This technology can be possibly applied for the development of unconventional reserv","PeriodicalId":143392,"journal":{"name":"Day 1 Tue, October 22, 2019","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124901131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Big Data in Field Development Projects","authors":"A. Gurianov, A. Katashov, K. Ovchinnikov, K. Saprykina, Igor Novikov, E. Malyavko, Vasily Kiselev","doi":"10.2118/196862-ms","DOIUrl":"https://doi.org/10.2118/196862-ms","url":null,"abstract":"\u0000 In recent years, new terms and concepts have appeared that describe the digital transformation currently in progress. The world image, including in the industrial world, has been changed by the concept of intelligent enterprise (IE) - a set of technological innovations, including artificial intelligence (AI), intelligent automation (IA), deep learning technologies, predictive analytics and cognitive computing. The increasing complexity of the oil and gas business and the decreasing optimization potential from traditional approaches require the use of new, innovative digital technologies to remain competitive.\u0000 Responding to the market conditions of falling hydrocarbon prices, the oil and gas industry is increasingly mastering Big Data to optimize technological processes and prevent accidents. The emergence of Big Data technologies, predictive analysis and machine learning are changing the general image of many industries, and the oil and gas industry is no exception. New players are quickly emerging throughout the industry, and digitalization will affect the entire value chain throughout in the oil and gas industry. Among the most promising segments for the transition to digital technologies are asset management and infrastructure facilities, field development, geophysical services, pipelines and processing.\u0000 Digital technology is the most powerful driver for cost reduction. It is expected that implementing these solutions will, by 2030, reduce the costs of E & P projects by up to 30%. Thus, Russia can leverage these new technologies and retain a share in the world energy market for another 50 years. The oil industry has recently passed the most difficult period in the last 30 years. The fall in oil prices since 2014, the reduction of 350 thousand employees worldwide, and fall in production investment are examples of serious challenges that the industry has faced in recent years. These challenges have resulted in new attempts to optimize business through implementing new technologies to improve the efficiency and profitability of companies.","PeriodicalId":143392,"journal":{"name":"Day 1 Tue, October 22, 2019","volume":"2010 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127340650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assisted History Matching for Reservoir Simulation Models","authors":"V. Syrtlanov, Y. Golovatskiy, I. Ishimov, N. Mezhnova","doi":"10.2118/196878-ms","DOIUrl":"https://doi.org/10.2118/196878-ms","url":null,"abstract":"\u0000 The paper presents assisted history matching methods for the preparation and modification of the simulation model parameters (absolute permeability, relative permeability, etc.)). The proposed approaches allow both to speed up the history matching process and improve the accuracy of the simulation results.","PeriodicalId":143392,"journal":{"name":"Day 1 Tue, October 22, 2019","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115447762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Water Alternating Gas Pilot Design and Results: Yaraktinskiy Field Eastern Siberia","authors":"D. Burdakov, D. Wolcott","doi":"10.2118/196769-ms","DOIUrl":"https://doi.org/10.2118/196769-ms","url":null,"abstract":"\u0000 The article describes the design of water alternating gas (WAG) project and the results of implementation within a portion of the Yaraktinskiy field. The technical applicability of using WAG to increase oil recovery was justified from core flood and slim tube experiments in conjunction with PVT fluid studies. The equation of state was tuned to the PVT data and slim tube experiments. Fully compositional modeling was used to generate type curves that demonstrated additional recovery from the WAG process. A systematic criterion was developed to identify and rank the best patterns for WAG response and therefore identify the optimal pilot area. For flood management performance ratios and efficiency criteria were defined.\u0000 Pilot response has provided additional recovery, indicating mobilization of previously immobile oil. History matching the pilot response has improved the model and this has been used to justify further scaling of the process to more areas of the field. As well, the model is now used to establish requirements for piping, compressor and other surface upgrades.","PeriodicalId":143392,"journal":{"name":"Day 1 Tue, October 22, 2019","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128711171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Horizontal Wells Geosteering and Reservoir Characterization by Using Advanced Mud Logging on the Example of the Terrigenous Reservoir of Eastern Siberia","authors":"A. Rotaru, A. Kushnikov, V. Vorobyov, M. Podberezhnyy, V. Bakhursky, R. Khalikov, V. Fagereva, D. Partyko","doi":"10.2118/196960-ms","DOIUrl":"https://doi.org/10.2118/196960-ms","url":null,"abstract":"\u0000 This paper presents the utilization of advanced mud logging to support drilling of horizontal well on the Ignyalinsky license area of Eastern Siberia. The advanced mud logging complex includes specialized software for recording and analysing geological and technical drilling parameters; technological sensors for registration of drilling parameters with the permissible limits of errors no more than 1%; advanced gas logging by using a high-resolution chromatograph at suction and return lines; geochemical analysis devices for XRF, XRD cuttings analysis and natural gamma radiation analysis of cuttings; the use of cuttings weighing machines to quantify the degree of the wellbore cleaning. This article discusses the application of listed data for geosteering and clarifying the geological model of the reservoir.\u0000 The lithological analysis of cuttings is carried out on the base of mineral and elemental cuttings composition, which, unlike field data of a standard mud logging survey, exclude the concept of \"human factor\" during analysing the lithology of cutting samples.\u0000 The data on mineral and elemental composition of wells were interpreted to clarify the lateral variability of the reservoir and to highlight potential reservoir intervals. Advanced gas logging was used to identify potential reservoir interval in pilot well, and consequently to plan MDT works.\u0000 Data on elemental composition of cuttings sample from pilot section and from core analysis of nearby exploration wells were used to construct geochemical profile of the reservoir. Furthermore, reference chemical elements were selected to mark the well position in the reservoir: exit above or beneath the target interval. XRF elemental analysis while drilling was used to improve borehole position in conjunction to LWD data.\u0000 The elemental composition of cuttings of horizontal well were used for facial interpretation, which is not captured by LWD tools. So, ancient fluvial channel bodies were identified on the base of geochemical rock typing, and potential reservoir intervals are suggested. The performed interpretation was verified by the resultsof the multistage hydraulic fracturing.","PeriodicalId":143392,"journal":{"name":"Day 1 Tue, October 22, 2019","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126557473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}