bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of Pressure Interference Test Without Stopping the Well Stock to Regulate the Process of Field Development of the NOVATEK Group of Companies
Authors: Dvinskikh Kristina , Zavalin Fedor , Naimushin Anton , Abdrakhimov Aleksandr 
Published: September 2020

Abstract
The main objectives of field development are to maintain high profitability, as well as to achieve the highest coefficient of oil recovery (COR). One of the ways to ensure a high COR for oil fields is creation of a reservoir pressure decrease system (RPD). So, for example, when create a system of RPD, the COR can reach 0.5 d. q., and without RPD - only 0.1-0.2 d. q In the case of designing the development of oil fields with a complex geological structure (the presence of a gas cap, block structure of the Deposit, a large number of faults), the complexity of the task of choosing the optimal development system increases significantly.
In Russia and in the world, there are a considerable number of oil fields that have been developed for a long time on the depletion mode, which has led to the formation of a considerable volume of the free gas phase. Such deposits often pass into the category of problematic and are characterized by low current values of the coefficient of oil recovery (COR), as well as the lack of reliable technological solutions for their effective development. Examples include the Talinsky area of the Krasnoleninsky field, the oil pool in the Jurassic sediments of the Novogodnee Deposit, and others. When the pressure increases further, for example, by pumping water, modeling the development of such deposits requires the use of non-equilibrium hydrodynamic models.
Application of the results of the pressure interference test (PIT) allows us to obtain valuable information about the connectivity of inter-well intervals, a quantitative assessment of the conductivity of reservoir faults, and, consequently, reduce risks when planning field development, increase the efficiency of ongoing geological and technical measures and their profitability. Conducting of PIT on a working stock, in comparison with classical methods, allows you to minimize the loss of production during research. Proper planning of field development with the involvement of PIT results, in particular-the introduction of the RPD system, allows to increase the COR and profitability of the development system as a whole.
The paper shows the results of the pressure interference test studies for a tectonically complicated structure of an oil and gas condensate field. Based on the results of the research, the efficiency of the existing RPD system was evaluated and decisions were made to transfer production wells to injection, taking into account the assessment of the risks of water breaks through conducting faults. In addition, the results of the pressure interference test were combined with the results of tracer studies. The convergence of research results by both methods is shown.
Smart Completion Improvement in Horizontal Wells Based on Through-Barrier Diagnostics
Authors: Solovyev Timur , Ivanov Alexander , Soltanov Dzheykhun , Meshkov Victor , Kamalov Artur , Nagimov Vener , Trusov Alexander , Aslanyan Irina , Makarov Dmitry 
Published: September 2020

Abstract
The complex interbedded heterogeneous reservoirs of the Severo-Komsomolskoye field are developed by horizontal wells in which, as part of the pilot project's scope, autonomous inflow control devices (AICD) are installed to prevent early coning and gas breakthroughs in long horizontal sections and reduce sand production, which is a problem aggravated by an extremely low mechanical strength of the terrigenous deposits occurring in the Pokur formation of the Cenomanian stage in this area.
The zones produced through AICDs are separated by swell packers. The issue of AICD effectiveness is discussed in the publications by Solovyev (2019), Shestov (2015), Byakov (2019) and some others.
One of the methods used for monitoring horizontal sections with AICDs is production logging (PLT). However, due to the complexity of logging objectives, the use of conventional logging techniques makes the PLT unfeasible, considering the costs of preparing and carrying out the downhole operations.
This paper provides some case studies of the Through-Barrier Diagnostics application, including passive spectral acoustics (spectral acoustic logging) and thermohydrodynamic modelling for the purpose of effective estimation of reservoir flows behind the liner with AICDs installed and well integrity diagnostics.
As a result of the performed diagnostics, the well completion strategy was updated and optimised according to the log interpretation results, and one well intervention involving a cement squeeze with a straddle-packer assembly was carried out.
Development of an Approach for Well Testing in Real Time
Authors: Pityuk Yulia Airatovna , Akmurzina Guzel Raifovna , Davletbaev Alfred Yadgarovich , Azarova Tatyana Petrovna , Farger Dmitriy Vladimirovich , Krivulyak Aleksandr Sergeyevich , Zyleva Svetlana Afanasevna 
Published: September 2020

Abstract
Effective management of field development requires continuous monitoring of the hydrodynamic parameters of the reservoir and wells. One of the sources of such information is the results of interpretation and analysis of well test. The aim of the work is to increase the quantity and quality of well test, which can be achieved by automating their conduct and the operational processing of field data and events at the wells. The present work describes the concept of well testing in real time, the development and implementation methods for searching candidate wells and algorithms for giving expediency estimation for well testing.
Implementation of automation of the production process for well test can be divided into several successive stages: searching for wells for well testing, giving expediency estimation of the well test with the issuance of recommendations, making decisions about the well testing, monitoring well testing, completion and interpretation of the well test. Each stage requires a methodological and algorithmic study for all types of well test. Candidate wells are searched by identifying the shutdowns and monitoring wells. Expediency estimation algorithm of well test includes calculating the duration of well test and production and injection losses, checking changes in well operating conditions, analyzing the conditioning of field data, and planned and completed well activities, including previously well tests and intersection with the well test program.
Moreover, an analysis of the business processes of well testing showed that all research methods require automation of routine operations of analysis and preparation of field data from sensors of downhole telemetry systems. For this purpose, a service-oriented application for real-time well testing is being developed. The present software allows one to optimize the well test program with the inclusion of unscheduled well test, to increase the number of studies without increasing the losses in production and injection, and to increase the coverage of measurements and the effectiveness of monitoring field development.
Summary of Application Results and Prospects for the Further Implementation of Simultaneous-Separate Operation in Slim Hole Wells and Simultaneous-Separate Operation for Three Development Locations
Authors: Yakovlev Alexandr Alexeevich 
Published: September 2020

Abstract
This paper describes the results of application and prospects for the further implementation of simultaneous-separate operation equipment in slim hole wells and simultaneous-separate operation equipment for three development locations in wells of Territorial production enterprise «TatRITEKneft».
The First for Russian Oil Company State of Art Intelligent Completion System Real Time Cleanup Monitoring and Optimization for 3 ERD wells in Caspian Offshore
Authors: Golenkin Mikhail Yur'evich , Biakov Aleksandr Petrovich , Eliseev Denis Vladimirovich , Zavyalov Aleksandr Aleksandrovich , Zhirkina Anna Andreevna , Pico Yamid Lopez , Shapovalov Alexey Petrovich , Bulygin Igor Aleksandrovich , Yakovlev Ivan Mikhailovich 
Published: September 2020

Abstract
For the first time Russian oil company has applied a new generation intelligent completion system in the Caspian offshore; the system can measure zonal phasic flow rates, fractional composition of the flow, zonal water cuts, pressures and temperatures. This equipment allowed to perform well cleanup with the new strategy, making optimization in the real time. This article describes experiences of running these operations, which are unique both for the Russian and for the world industry.
Since the technical resources in offshore field development are limited, it used to be impossible to run a thorough cleanup and assure the production of ERD wells at optimal level of performance. It states question about the practicability of long wells drilling. Three ERD wells in the Caspian offshore were the first ones where the Russian oil company used a unique all-electrical intelligent completion system. The system includes the flow control valve with infinite number of positions and the set of downhole sensors that provide a unique composition of measurements – pressure, temperature, phasic flow rates, fractional composition of the flow for each zone individually. Novel technology opened an opportunity to optimize the cleanup process by cleaning every zone separately. Meanwhile, it became possible to understand the extent to which every zone is cleaned and in real-time optimize the process by increasing the drawdown in the undercleaned zones.
New methodology to speed up cleanup process, test and commission the well was designed. It is a crucial aspect for the wells that are drilled from an offshore drilling rig. Currently there are 5 wells in Russia and 9 of them in the world where the cleanup operations were performed with the use of described completion technology.
Methodology and technology that are described in the article are innovative for the world industry. Interpretation of the expanded dataset that was obtained from the downhole sensors used to be unavailable for general use during the cleanup and it is described for the first time using an example from several wells.
Practices, experiences and technology described in the article will be useful for the field engineers, reservoir engineers and specialists who make decisions related to planning and organizing the operations both for the offshore and onshore fields.
Oil Rim Water Flooding Improvement Experience
Authors: Ilikbaev Valeriy Vitalievich , Virt Vitaliy Igorevich , Kulikov Iurii Victorovich , Kosolapov Vladimir Olegovych , Kazykhanov Rustam Ilusovich , Varavva Valentina Yuryevna 
Published: September 2020

Abstract
The paper describes an approach to the analysis of the efficiency of water flooding in relation to the development of the oil rim. The ways of optimizing the existing water flooding strategy are shown based on the actual operation of the wells and the forecast based on the hydrodynamic model. The issues of monitoring and control are considered as well as monitoring the operation of injection wells with the aim of subsequent operational decision-making regarding their operating modes.
Experience of the Autonomous Inflow Control Devices Application at the Oil-Gas-Condensate Field to Control Early Gas Breakthroughs
Authors: Meyer Elena , Bormashov Dmitry , Shkred Vitaly , Malofeev Mikhail , Oparin Ivan , Mayorov Andrey 
Published: September 2020

Abstract
Development of oil rims at oil-gas-condensate fields is accompanied by a high risk of gas coning which leads to well productivity losses followed by conversion of such wells to an idle stock. In order to increase the oil recovery factor of oil rims and to eliminate early gas breakthroughs, horizontal wells drilled in thin oil rims are equipped with autonomous inflow control system.
The study describes the experience of AICD application for one of the largest fields in East Siberia with an oil rim and a large gas cap, where an integrated analysis of the AICD well performance was conducted for the first time in Russia. This analysis includes: choosing well-candidates, performing AICD lab testing, sector reservoir simulation, modeling of AICD effect, followed by the actual well performance analysis after running AICDs. All this became possible due to the well-organized cooperative work of the operator and the contractor.
The wells included in this study were successfully put into production at lower GOR values compared to their surrounding wells
Experience of Downhole Microseismic Monitoring of Reservoir Waterflooding in Baitugan Field
Authors: Naumov Yury Anatolyevich , Tupitsyn Andrey Mikhailovich , Enachesku Cristian , Fedoseev Maxim Alekseevich , Lavrenkova Natalia Viktorovna , Mitin Alexey Vladimirovich , Kalvan Lyubov Viktorovna 
Published: September 2020

Abstract
The paper presents the experience of using downhole microseismic monitoring to determine the direction of working agent losses while maintaining formation pressure in Baitugan oil field in Orenburg region. Studies were aimed at history matching and elaboration of the further strategy for formation pressure maintenance (FPM) and field development as a whole.
The seismic monitoring method was used in the downhole version, when observations are done from the observation well located nearby the injection one. For reliable recording of weak microseismic events, high sensitivity receivers were used with 4 sensors per component. A special injection program was developed. Its first stage consisted in optimization of modes that ensure the maximum injection into formation of a fluid supplied at the wellhead.
During acquisition parameter testing, passive recording of the seismic signal was done at all stages of injection during two weeks in various modes, including a short-term stop of injection with subsequent increase in injection to a maximum injection rate with exceeding the fracture gradient. Fracture growth zones were identified below the target formation. Starting from the second week of recording, fracture propagations to the overlying formations were observed under increased injection pressure. Based on data obtained, a three-dimensional map of microseismic events recorded in the formation was created. It was used for interpretation and allowed to specify geometry of self-induced hydraulic fractures depending on injection modes.
Microseismic mapping of self-induced fractures in injection wells was done in Russia for the first time. The results of observations allow to optimize the formation pressure maintenance system through optimizing injection modes depending on local fracture gradients and injection shutting off in the zones with uncontrolled self-induced fractures that develop under minimum wellhead pressures. The obtained data also make it possible to significantly improve quality of history matching for carbonate deposits with reduced formation pressure through determining the injection efficiency. This result directly improves both the quality of forecast analysis and economic impact of formation pressure maintenance.
Modeling of Wax and Salt Deposition in the Near-Well Zone of a Low-Temperature Reservoir Under Various Operating Conditions of Wells
Authors: Gaidukov Leonid Andreevich 
Published: September 2020

Abstract
A number of saline low-temperature reservoirs in Eastern Siberia are characterized by the development of damage effects of the reservoir pore space with filtered solid particles, which are formed as a result of two specific reservoir processes: the phase transition of wax contained in oil; salt precipitation when the highly mineralized front of the injected water breaks through toward production well. These effects are most intense in the near-well zones of producing wells and are initiated by technogenic changes in thermobaric conditions and the release of dissolved gas from oil. As a result, the productivity of wells is dynamically reduced. To design effective measures to restore well productivity, it is necessary to understand the structure of the borehole zone and the dynamic mechanisms of technogenic changes in its filtration properties. For these purposes, the article developed a specialized mathematical model of wax deposition in the pore space of a low-temperature oil reservoir and a model of solid salt precipitation during filtration of extremely saturated NaCl salt solution, which allow calculating the technogenic change in the permeability of the near-well zone of the producing well during its operation.
Complex Approach to Optimization of Brownfields Business Cases Based on the Pilot Project Renovation in PJSC Gazprom Neft
Authors: Asmandiyarov Rustam Nailevich , Monzherin Mikhail Aleksandrovich , Zenov Anton Aleksandrovich , Drofa Pavel Mikhailovich , Ribakov Roman Aleksandrovich , Malcev Nikita Valerievich , Lozina Polina Sergeevna , Veselov Valeriy Mikhailovich 
Published: September 2020

Abstract
The paper considers a new approach to working with mature fields, assessing the effectiveness of current development, searching and forming case studies on optimization of development and associated costs.
The approach is based on several consecutive steps:
– the most accurate understanding of the composition of current costs, their correct accounting for calculating the profitability of the well stock, – the definition of low-profit wells and clusters, – search and evaluation of measures to optimize the development system and work with the wells, – search and assessment of possible measures to reduce existing costs based on best practices.
In the framework of the described methodology, each individual producing well is considered as an independent business unit, the combination of which ultimately forms the overall economy of the field. The field, in turn, is considered as a closed system of the well - wellbore - BPS / CPS, each of whose elements is interconnected.
The results of applying this approach are presented on the example of the Renovation pilot project, within the framework of which a number of optimization cases were formed and successfully implemented at one of the fields of Gazprom Neft PJSC.
Also, during the implementation of the project, a tool program was created that allows economic evaluation of all possible activities in the logic described above, to assess the impact of each element of the system on each other as a result of the implementation of the events.
Thus, a new algorithm has been formed and partially automated for continuous monitoring of current production at the field, identifying "problem" areas and the formation of optimization measures for such areas.
Decision Support System for Tight Oil Fields Development Achimov Deposits and Their Analogues Using Machine Learning Algorithms
Authors: Fedorov Aleksei Eduardovich , Povalyaev Andrey Aleksandrovich , Suleymanov Bulat Ildarovich , Dilmuhametov Ilshat Rashitovich , Sergeychev Andrey Valerievich 
Published: September 2020

Abstract
The aim of this work is to develop an approach to multivariate optimization of development systems for tight oil reservoirs of the Achimov formation, where large volumes of drilling of RN-Yuganskneftegaz LLC are currently concentrated on. The approach described in the paper is an integral part of the corporate module "Decision Support System for drilling out new sections of tight oil reservoirs", which allows making quick design decisions for new drilling sites of target objects.
This work discusses the main parts of the integrated solution of this system that will be embedded into corporate software.
Also, the description of the global approach and obtained results are presented. The main idea of this project is based on automatic assignment of the prospective development zone to an existing cluster-analog, based on well logs response in exploration wells. Following this interpretation, the potential performance of various development systems is evaluated and the optimal one is selected.
Within the framework of these projects the following tasks were solved:
Wells clustering in Achimov deposits and their analogs. The geological heterogeneity and reservoir connectivity were characterized and a special algorithm for wells assignments to an existing cluster was developed, that is done by: Wells clustering depending on their petrophysical properties derived from well logs interpretation via k-means algorithm. Wells classification with a use of neural network. Multivariate 3D dynamic modeling and creation of surrogate models to provide predictions of reservoir simulation results. Development of the software package with all mentioned functionality being implemented.
Deep Neural Network for Real-Time Location and Moment Tensor Inversion of Borehole Microseismic Events Induced by Hydraulic Fracturing
Authors: Wamriew Daniel Stephen , Charara Marwan , Maltsev Evgenii 
Published: September 2020

Abstract
Locations and source mechanisms of microseismic events are very crucial for understanding the fracturing behavior and evolution of stress fields within the reservoir and hence facilitates the detection of hydraulic fracture growth and estimation of the stimulated reservoir volume (SRV). In the classic workflow, there are two main methods for locating microseismic events with a calibrated fixed velocity model: grid search and linear inversion. The grid search is very stable; can find a global minimum and does not need initial event locations. However, it is computationally intensive and its resolution depends on the grid size, hence, it is not suitable for real-time monitoring. On the other hand, although the linear inversion method is quite fast, the inversion may be pushed into a local minimum by thin shale layers and large velocity contrasts leading to false locations. The source mechanisms of the located events, which provide information about the magnitudes, modes and orientations of the fractures, are obtained through moment tensor inversion of the recorded waveforms. In this paper, we propose a deep neural network approach to solve the above challenges, in real-time, and increase the efficiency and accuracy of location and moment tensor inversion of microseismic events, induced during hydraulic fracturing. Location of microseismic events was considered as a multi-dimensional and non-linear regression problem and a multi-layer two-dimensional (2D) convolutional neural network (CNN) was designed to perform the inversion. The source mechanisms of the microseismic events were inverted using a multi-head one-dimensional (1D) CNN. The neural networks were trained using synthetic microseismic events with low signal to noise ratio (SNR) to imitate field data. The overall results indicate that both the 2D CNN and 1D CNN models are capable of learning the relationship between the events locations and source mechanisms and the waveform data to a high degree of precision compared to classical methods. Both the event location and source mechanism errors are less than few percent. Deep learning offers a number of benefits for automated and real-time microseismic event location and moment tensor inversion, including least preprocessing, continuous improvement in performance as more training data is obtained, as well as low computational cost.