bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating Efficiency of Multilateral Producing Wells in Bottom Water-Drive Reservoir with a Gas Cap by Distributed Fiber-Optic Sensors and Continuous Pressure Monitoring
Authors: Maltsev Andrei Konstantinovich , Kudlaeva Nailia Vladimirovna , Aslanyan Artur Mikhailovich , Krichevsky Vladimir Markovich , Gulyaev Danila Nikolaevich , Surmasheva Leysan Vladislavovna , Solovyeva Viktoria Vitalievna 
Published: October 2021

Abstract
The main goal of the pilot job is to assess the risks of production by horizontal wells and multilateral wells with a close gas cap above and water layers beneath the main formation. The objectives are to monitor the total producing length of the wells using temperature and pressure surveillance. The results of monitoring were analyzed at different stages of development.
An analysis was carried out by combining pressure and temperature data obtained while monitoring the production of multilateral wells. The well properties were determined using RTA and PTA.
To assess the inflow profile, distributed temperature sensors in the wells were analyzed for the entire period of appraisal production. A feature of the research was the low contrast of temperature anomalies associated with fluid inflow. In addition, it was also revealed that the DTS absolute readings at the depth of the formation were affected by surface temperature, which required corrections and the use of relative readings in the calculations instead of absolute ones.
The main feature of the pressure analysis was the short period of production. With such well completion geometry and reservoir properties of the layer, the radial flow could not be achieved during the whole test period. Despite these limitations, the dynamics of the total producing length of the well was determined. The initial value of the producing length was about 70% of the drilled length, then there is a slight decrease after 7 to 10 months of well production.
By analyzing the fiber-optic temperature profile, an inflow profile was assessed. Based on the analysis of changes in relative temperature anomalies, the shares of inflow from the sidetracks were estimated.
Several memory temperature / pressure gauges set along the horizontal section were used as an additional data source to monitor well parameters during the whole period of production. The difference in their readings was due to, among other things, the average flow rate in the section between the sensors, which made it possible to give an independent assessment of the inflow profile.
Based on the results of the job performed, a number of risks and uncertainties were removed, including information on the total flowing horizontal length dynamics, which is a valuable input for full-field development planning. In addition, an express method of DTS data analysis has been developed for assessing the wellbore producing length without significant temperature changes associated with intervals of inflow.
Novel Integrated Approach for Complex Carbonate Reservoirs Testing with Wireline Formation Tester: Yurubcheno-Tokhomskoye Field Cases Study
Authors: Dzhalatyan Yakov , Charupa Mikhail , Galiev Aydar , Karpekin Yevgeniy , Egorov Sergey , Kishauov Abilkassym , Smetanin Yury , Pushkarskiy Alexey , Arbatsky Timur 
Published: October 2021

Abstract
In the presented paper, the object of the study are carbonate rocks of the Riphean and clastic-carbonate rocks of Vendian-Cambrian ages, uncovered by the well drilled at Yurubcheno-Tokhomskoye field.
These reservoirs are characterized by extremely low porosity (1-4%) and determining saturation nature and fluid contacts cannot be reliably solved by conventional wireline petrophysical logging. Solutions to these problems are provided by interval testing using wireline formation evaluation testing tool (WFT). However, to obtain quality results from WFT testing it is important to identify porous intervals first by using advanced wireline logging services which are sensitive to porosity and fractures.
In order to select the optimal WFT toolstring combination and to prospective testing intervals, advanced petrophysical wireline logging suit ran first. Porous reservoirs were identified from density, neutron and nuclear magnetic resonance evaluation. Saturation evaluated through dielectric and induction-based resistivity logging.
In fracture-vug type reservoir, the main inflow of formation fluid into the well is provided from fractures, so it was very important to allocate conductive fractures to plan test intervals for WFT accordingly.
based on imagers evaluation, fractures and faults were visualized; using Stoneley's wave conductive fractures, not clogged with drilling mud solids were identified; borehole acoustic reflection survey was used to segregate large fractures that propagated in the reservoir;
During WFT logging, a total of 23 intervals were tested, for 8 of which reservoir fluid inflow was achieved, in all others, mainly with low porosity or single non-conductive fracture, the inflow was not achieved or was insignificant.
According to the results of WFT testing, the nature of saturation for clastic-carbonate sediments of Vendian age was determined. Inflow of formation fluid (oil and water) from Riphean fractured reservoirs was achieved from 6 intervals, with identified fractures according to described above advanced logging suit. In addition, pressure transient analysis was performed, to measure the formation pressure, define pressure gradient curves and assess the fluids contact level with high confidence, for the first time for this field.
End-to-End Quality Control of Downhole Samples from the Sampling Point to the Laboratory Unit: This is Possible and Necessary
Authors: Lobanov Alexey Alexandrovich , Fedorovskiy Stanislav Alexandrovich , Promzelev Ivan Olegovich , Tikhomirov Yevgeny Vladimirovich , Zvonkov Mikhail Alekseevich , Kovalenko Vyacheslav Andreevich , Kuporosov Dmitriy Nikolaevich , Bastrakov Aleksandr Aleksandrovich , Nartymov Vladimir Sergeevich , Harisov Arthur Uzefovich , Struchkov Ivan Alexandrovich , Pleshanov Nikolay Nikolaevich , Makarov Sergey Evgenievich , Frolov Artem Sergeevich 
Published: October 2021

Abstract
The services and downhole sampling technologies market in Russia is in deep stagnation. The objective conditions have emerged, wherein the responsibility and leadership in the development and recovery of this area is a prerogative task of major oil and gas companies, rather than the equipment manufacturers. The paper shares the authors’ experience in the development, pilot testing and implementation of novel regulatory and technical approaches and technologies of sampling, transportation, field, end-to-end and laboratory assessment of samples quality in PJSC «Gazprom Neft».
The Efficiency of the Novel Technology Reservoir Pressure Reconstruction Without Well Shut-in and without Production Losses
Authors: Belyakov Alexander Alexandrovich , Gulyaev Danila Nikolayevich , Krichevskiy Vladimir Markovich , Nikonorova Anastasia Nikolaevna , Iskibaev Roman Edisonovich 
Published: October 2021

Abstract
The analyzed oi- gas field is based around Orenburg region, located 40 km away from the Buzuluk city, Russia.
This multi-layered field has a number of domes. 11 productive layers lie within its cross-section. In total, 21 oil and two gas deposits have been identified at this field.
The study layer A4 is confined to the top of the Bashkir layer and has a wide extension. Permeable rocks at this layer include limestone and dolomite, separated by impermeable sublayers. The effective oil-saturated well thicknesses vary between 1.1-38.4 m, and is 11.8 m on average. The caprock of the formation A4 consists of the Vereiskan clay-siltstone sequence.
Optimized Multi-Zone Dynamic Reservoir Evaluation in the Middle Caspian
Authors: Shtun Sergey , Kaipov Yermek , Kamalov Fanise , Akbayev Beibit , Blinov Vlad 
Published: October 2021

Abstract
Caspian offshore is reach for hydrocarbon reserves. The fields are made of multi-zone carbonate and sandstone reservoirs with significant variation of properties having high pressure (HP), high temperature (HT) and high H2S concentration in reservoir fluid. These challenges pose significant challenges to conduct the formation and multi-zone reservoir testing in a safe and informative manner.
The dynamic reservoir evaluation program consists of formation pressure and its profile measurements, fluid pump-out for confirming the fluid type and sampling performed with wireline formation testers (FT) in open-hole and multi-zone well test for productivity estimation with drill-stem test (DST) designed for offshore environment with HP and high H2S.
The project was planned and executed in an integrated manner, where the well construction design and selection of drilling and completion fluids has to improve the chance of success for FT and DST by taking into accound the downhole tool sizes and complex geological conditions.
The open-hole formation testing and well testing in cased-hole were combined to provide enough information for characterizing multi-zone reservoirs by minimizing the drilling rig time. The well testing program was optimized in terms of number of zones for testing and necessity to acidize the reservoir based on formation testing data.
The given methodolgy allowed to efficiently conduct the formation testing and well testing at two recently drilled offshore wells with multi-zone reservoirs.
It was the first integrated dynamic reservoir evaluation project for such complex geological conditions in Middle part of Caspian offshore. This paper demonstrates the lessons learnt from two wells and offers the methodology for planning the evaluation for similar fields.
Comparative Analysis of Tracers Against Pressure Pulse Code Interference Testing based on the Numerical Simulations of the Synthetic Oilfields with Complicated Geology
Authors: Aslanyan Artur Mikhailovich , Farakhova Rushana Rinatovna , Gulyaev Danila Nikolayevich , Mingaraev Ramil Anvarovich , Khafizov Ruslan Ildarovich 
Published: October 2021

Abstract
The main objective of the study is to compare the results of the cross-well tracers survey against the pulse code pressure interference testing (PCT) for the complicated geological structures.
The study was based on the numerical simulations on the synthetic 3D models with popular geological complications, such as faults, vertical and horizontal reservoir anisotropy and pinch-outs.
The study has set a special focus on quantitative analysis of the reservoir properties estimated by tracers and PCT as against the known values.
This provides a text-book examples of advantages and disadvantages of both surveillance methods in different geological environment.
Pulse code testing is specific implementation of pressure interference testing by creating a series of injection/production rate changes accordingly to a preset schedule to create a "pressure code" and monitoring the pressure response in the offset wells. The use of high-resolution quarts gauges is highly beneficial in case of large cross-well intervals scanning or poor reservoir quality in case of regular inter-well spacing.
The tracer survey is based on injecting a liquid with chemical markers and subsequent capturing the markers at surface samples in the offset wells. The modern markers are relatively cheap and can be captured at very low concentrations thus making the cross-well scanning available even for high inter-well spacing.
For synthetic models with vertical inhomogeneity the PCT provides a close estimate for compound dynamic reservoir properties (transmissibility and pressure diffusivity).
For synthetic models with lateral inhomogeneity the PCT provides an accurate estimation for effective reservoir thickness and permeability.
Tracers survey is not able to assess the reservoir thickness.
The popular methods to assess reservoir permeability from tracers survey show a substantial deviation from the true reservoir permeability for synthetic models with vertical and lateral heterogeneity.
This leads to conclusion that the most reliable application of racers survey is a qualitative assessment of cross-well connectivity and quantitative estimate of permeability in homogenous reservoirs.
The first study of quantitative comparison of tracer survey against pressure pulse-code interference survey. Tracer survey and PCT efficiency was compared on 3D numerical models. Presence of synthetic models, describing geological complications, which may be seen very often on real reservoirs, provides a reliable basis for comparison.
Localisation and Recovery Planning of the Remaining Hydrocarbon Reserves
Authors: Aslanyan Artur Mihailovich , Popov Arkadii Yurievich , Zhdanov Ivan Aleksandrovich , Pakhomov Eugeny Sergeevich , Ibryaev Nikolay Petrovich , Kuznetsov Maksim Aleksandrovich , Krichevsky Vladimir Markovich , Garnyshev Marat Yurievich , Guss Rodion Vladimirovich 
Published: October 2021

Abstract
The paper presents the results of a study project of 60+ well block of the large (&gt; 1,000 wells) mature (30 year old) oilfield in Western Siberia with objective to localise and characterize residual recoverable reserves and propose the optimal economic scenario for further depletion.
Low permeability, heterogeneous reserve structure along the cross-section, numerous induced hydraulic fractures in producing wells and numerous spontaneous fractures in injecting wells with dynamic behavior, aggravated by numerous behind-the-casing crossflows in almost every well have resulted in a very complex conditions of remaining reserves.
The conventional methods of production analysis and surveillance (well testing and production logging) do not provide a consistent picture of the current distribution and conditions of the remaining reserves and required a deeper and more complex analysis.
Development Opportunities Management workflow was chosen for this particular holistic study, which includes a set of interconnected studies, field surveillance, geological and flow modelling and culminated in field development planning based on the digital asset twin. (Ganiev, B., 2021)
Digital asset twin was constructed based on results of this workflow with a full-range economical model, flow simulation over the thoroughly calibrated fine-grid 3D dynamic model and production complication model (dynamic behavior of the fractures and behind-casing channeling).
The 3D model has been calibrated on results of the cross-well pressure-pulse surveillance, reservoir-oriented production logging and was validated by the results of the drilling of the transition wells.
The digital asset twin was used to find the optimal investment scenario based on multivariate calculations with the help of digital assistants.
Due to simplicity of the user interface and client-server design, the digital twin was made available for various corporate engineers and managers without any modelling skills to play around with their own ideas on possible production/investment scenarios which gave another level of validation of the ultimate field development plan.
All activities carried out within the digital twin automatically generate a complete package of investment metrics (NPV, PI, IRR, MIRR, Cash Flow and many correlation graphs) to assess the economic efficiency of each package and select the most appropriate solution for further ultimate choice.
The approved scenario was based around drilling 6 producing side-tracks in specific locations/trajectories, performing workovers on specific offset injectors and re-scheduling of the production/injection rates in all block wells.
The results of the field development's activities implementation will be the subject of a future publication.
Stuck Pipe Early Detection on Extended Reach Wells Using Ensemble Method of Machine Learning
Authors: Rakhimov Rushad Ravilievich , Zhdaneev Oleg Valerievich , Frolov Konstantin Nikolaevich , Babich Maxim Pavlovich 
Published: October 2021

Abstract
The ultimate objective of this paper is to describe the experience of using a machine learning model prepared by the ensemble method to prevent stuck pipe events during well construction process on extended reach wells. The tasks performed include collecting, analyzing and cleaning historical data, selecting and preparing a machine learning model, testing it on real-time data by means of desktop application. The idea is to display the solution at the rig floor, allowing Driller to quickly take actions for prevention of stuck pipe event.
Historical data mining and analysis were performed using software for remote monitoring. Preparation, labelling and cleaning of historical and real-time data were executed using programmable scripts and big data techniques. The machine learning algorithm was developed using the ensemble method, which allows to combine several models to improve the final result.
On the field of interest, the most common type of stuck pipe are solids induced pack offs. They occur due to insufficient hole cleaning from drilled cuttings and wellbore collapse due to rocks instability. Stuck pipe prevention on extended reach drilling (ERD) wells requires holistic approach meanwhile final role is assigned to the driller. Due to continuously exceeding ERD envelope and increased workloads on both personnel and drilling equipment, the effectiveness of preventing accidents is deteriorating. This leads to severe consequences: Bottom Hole Assembly lost in hole, the necessity to re-drill the bore and eventually to increased Non-Productive Time (NPT).
Developed application based on ensemble machine learning algorithm shows prediction accuracy above 94%. Reacting on alarms, driller can quickly take measures to prevent downhole accidents during well construction of ERD wells.
Optimization of the Reservoir Management System and the ESP Operation Control Process by Means of Machine Learning on the Oilfields of Salym Petroleum Development N.V.
Authors: Musorina Anastasia Dmitrievna , Ishimbayev Grigory Sergeyevich 
Published: October 2021

Abstract
Under the present conditions of oil and gas production, which are characterized by mature production fields and the focus shifted towards digitalization of production processes and use of machine learning (ML) models, the issues related to the improvement of accuracy and consistency of the well operation control data are becoming increasingly important. As a result, SPD has successfully implemented the project of using annular pressure sensors in combination with machine learning models to control the well annular pressure as part of the field development program compliance.
Under the field development program, echosounder and telemetry system readings are typically used to control the annular pressure and the dynamic flowing level. Echosounders, however, are not designed as measuring instruments, the accuracy of their readings being low and making it impossible to reliably evaluate the well's dynamic flowing level and annular pressure, as well as to achieve the well's maximum potential, and the telemetry systems used to measure the pump intake pressure may go wrong.
This manuscript describes the approach to the producer well annular pressure assessment based on the machine learning model data. The machine learning (ML) model is a function of the target variable (bottom-hole pressure), which is predicted on the basis of the actual data: static parameters (well schematic, pump design) and dynamic parameters (annular and line pressures, flowrate). The input parameter interpretation results in the most probable value of the target variable based on the historic data.
Multi-Mineral Segmentation of SEM Images Using Deep Learning Techniques
Authors: Alekseev Vladislav Vasilevich , Orlov Denis Mihaylovich , Koroteev Dmitry Anatolevich 
Published: October 2021

Abstract
The approaches of building and methods of using the digital core are currently developing rapidly. The use of these methods makes it possible to obtain petrophysical information by non-destructive methods quickly.
Digital rock physics includes two main stages: constructing models and modeling various physical processes on the obtained models. Our work proposes using deep learning methods for mineral and pore space segmentation instead of classical methods such as threshold image processing. Deep neural networks have long been able to show their advantages in many areas of computer vision.
This paper proposes and tests methods that help identify different minerals in images from a scanning electron microscope. We used images of rocks of the Achimov formation, which are arkoses, as samples. We tested various deep neural networks such as LinkNet, U-Net, ResUNet, and pix2pix and identified those that performed best in segmentation.
Long-Term Forecasting and Optimization of Non-Stationary Well Operation Modes Through Neural Networks Simulation
Authors: Ponomarev Roman Yurievich , Vershinin Vladimir Evgenievich 
Published: October 2021

Abstract
The article discusses the results of long-term forecasting of non-stationary technological modes of production wells using neural network modeling methods. The main difficulty in predicting unsteady modes is to reproduce the response of producing wells to a sharp change in the mode of one of the wells. Such jumps, as a rule, lead to a rapid increase in the forecast error. Training and forecasting of modes was carried out on the data of numerical hydrodynamic modeling. Two fields with significantly different properties, the number of wells and their modes of operation were selected as objects of modeling. Non-stationarity was set by changing the regime on one or several production wells at different points in time. The LSTM recurrent neural network carried out forecasting of production technological parameters. This made it possible to take into account the time-lagging influence of the wells on each other. It is shown that the LSTM neural network allows predicting unsteady technological modes of well operation with an accuracy of up to 5% for a period of 10 years. The solution of the problem of optimization of oil production is considered on the example of one of the models. It is shown that the optimal solution found by the neural network differs from the solution found by hydrodynamic modeling by 5%. At the same time, a significant gain in calculation time was achieved.