bluuebunny/crossref_metadata_2025_split huggingface dataset:
Peculiarities of White Tiger Field Basement Development Forecasting: Chsllenges and Solutions
Authors: Lubnin Alexandr , Afanasiev Igor , Yudin Evgeniy , Sansiev Georgiy , Galimova Anastasia 
Published: October 2018

Abstract
This paper presents a method for the basement development parameters forecasting for the main offshore production object of White Tiger field. Due to peculiarities of the basement geological structure and its development the conventional approaches to the production planning for this object have low forecasting ability. The authors have developed a relevant method to solve the issue of accurate basement development parameters forecasting. A model of the well's operation process was developed on the basis of the method of the pipe multi-phase flow parameters hydraulic calculations with account of correlational PVT-functions for water, oil and gas for the purpose of describing the downhole equipment. The material balance and displacement models were used to describe the reservoir development. As a result of unification of the implemented approaches to the reservoir development and well description a method which allows significantly improving the forecasting abilities of the calculations was obtained.
Building of Effective Control and Management System for Injection Horizontal Wells During Waterflooding
Authors: Galeev Rail , Rybakov Roman , Yakovlev Andrey , Kayeshkov Ilya , Simakov Sergey , Fayzullin Ildar , Sagirov Aleksandr , Feoktistov Roman , Suleymanov Ayyar 
Published: October 2018

Abstract
The main uncertainties in the field development with the use of multiple-fractured horizontal wells (MFHW) in waterflooding are the inflow/injection profile along the horizontal wellbore, the number of working hydraulic fracturing ports, the dynamics of the productivity factor, the presence of the self-induced fracturing effect. All these factors affect the sweep efficiency and oil recovery factor. To remove uncertainties and increase the efficiency of waterflooding, a systematic approach to the control and management of the MFHW is required.
Implementation of this approach is an important direction of technological development of Gazprom Neft PJSC. The creation of a system for monitoring and managing the MFHW is based on the search, sampling, analysis of efficiency and selection of control technologies (geophysical studies for removal of uncertainties) and management technologies (well interventions for improvement of operational efficiency of MFHW).
One of the most promising technologies for monitoring the MFHW is long-term monitoring of downhole parameters (temperature and noise) with fiber-optic systems (FOS). Gazprom Neft PJSC has a positive expirience in this area, which includes the use of the FOS of various configurations, design and interpretation of the results of this type of research. Therefore, the main issue of using FOS in MFHW is the delivery of optical fiber to the horizontal part of the well with the possibility of further carrying out the well interventions without dismantling the FOS. The paper describes the results of testing a unique method of delivery of fiber-optic cable in the MFHW using coiled tubing and hydraulic anchor at the field in the Orenburg region.
Implementation of an Integrated Approach to Develop Low-Productivity Reservoirs of the Priobskoye Field
Authors: Shurunov Andrey , Iakovlev Andrey , Sheremeev Alexander , Kaeshkov Ilya , Rastegaeva Elena , Suleymanov Ayar , Fayzullin Ildar , Kolupaev Dmitry 
Published: October 2018

Abstract
Horizontal multi-fractured wells nowadays are the most common way of low-permeability reservoirs exploitation either in Russian and foreign oilfields. Besides its high efficiency such completion has a lot of factors (usually undefined) which can together significantly decrease oil rate. Here some of them are listed: Drilled horizontal well length and producing well lengthNumber of created and producing fracturesFracture length by design and by the actual production and well-testFracture location in relation to well (azimuth and initialization interval).Interference between neighborhood wells through the fractures during injection and productionEtc.
The paper deals with most interesting parts of a complex project which purpose is to realize the multi-fractured well potential and production system diagnostics. There are three main issues in this paper:
Designing – filed-sector choosing, optimum spacing and well completion calculations
Realization – well construction and studies conduction
Analysis – comparison between new project wells and common wells in the neighborhood, geological and hydrodynamic model correction
Current primary project result is a significant exploitation system efficiency growth after a change of well and fracture directions (perpendicular to the wellbore). The secondary but anyway very important results are learned lessons and new competences in well construction and studies.
The Method of Express Estimation of Pore Pressure Map Distribution in Reservoirs with Faults and Wedging Zones
Authors: Yudin Evgeniy Viktorovich , Gubanova Anna Evgen'yevna , Krasnov Vitaliy Aleksandrovich 
Published: October 2018

Abstract
The analysis of the energy status of a reservoir having many faults and wedging zones is a significantly complex problem which has no engineering solutions at the moment. The presented paper is aimed at developing a convenient and quickly solving engineering tool to make an isobar map for the reservoirs where large numbers of faults and reservoir fringes are present.
For the purpose of the isobar map drawing a pressure distribution equation for the porous media is solved at every time step. The boundary element method was used as a mathematical basis. This method allows accounting for all types of the reservoir structure irregularities, including faults and wedging zones. The calculation using the boundary element approach is quite fast compared to the finite element method and the finite difference method because it decreases a dimension of the problem by one. The considered engineering instrument was implemented as a separate application using C++ coding language. The monthly well data, in particular bottom-hole pressures and flow rates, are used as initial information.
Standard engineering tools such as material balance fail to fulfill the problem of the isobar map construction for the reservoirs with large numbers of faults. This is due to the fact that the material balance method does not account for dimensional distribution of areas having significant influence on the filtration flows distribution (faults, wedging zones). Use of full-scale 3D hydrodynamic models is complicated by the uncertainty of location and conductivity of faults. This factor significantly decreases the viability of using of full-scale hydrodynamic models for quick engineering calculations in course of the formation energy status analysis. The purpose of this work is in establishing a convenient algorithm which would allow assessing the reservoir energy status with account of its structural uncertainties, including presence of faults and wedging zones, with engineering accuracy using minimum volume of field information. The paper describes the main approach to the development of a reliable and quick-calculation algorithm for constructing isobar maps with account of main reservoir structure uncertainties. The accuracy verification of the obtained map against the analytical solutions and the numerical modelling results from the commercial simulators was conducted.
The calculation speed allows solving operational production tasks, including faults conductivity assessment, pressure maintenance efficiency, aquifer activity identification, well interference degree determination. Application of the program is demonstrated on the examples of the terrigenous field offshore of Vietnam and carbonate field of Timano-Pechora oil and gas province. The proposed program also allows conducting the permeability assessment for the wells and tracking the skin-factor dynamics by means of comparative analysis of well data for various dates.
New Methodology to Quantify the Productivity of Hydraulically Fractured Multilateral Wells in Tight Oil Reservoirs with Gas-Drive
Authors: Eliebid Mohammed , Ahmed M. Elmuzafar , Al-Nuaim Sami 
Published: October 2018

Abstract
The main objective of this paper is predicting the inflow performance relationship (IPR) for hydraulically fractured multilateral wells in tight formations to measure the flow rate corresponding to the bottom hole flowing pressure distribution along the horizontal laterals and the fractures. Due to the unavailability of analytical solutions for two-phase and three-phase flow problems in vertical, horizontal and multilateral wells because of the complex variable phases distributions in the reservoir. To predict the performance of two and three-phase several empirical models pioneered by Vogel's equation are used to forecast the IPR of two-phase for vertical wells and his method has been modified for multilateral and horizontal wells. Furthermore, there is no model to predict the performance of hydraulically fractured oil wells. In this work, we present a two-phase hydraulically fractured well model utilizing modifications to the present IPR models for two-phase planner horizontal laterals wells.
The Method of Localization of Residual Oil on the Basis of Complex Multi-Well Diagnostics and Calibration of the Hydrodynamic Model
Authors: Zhdanov Ivan , Kotezhekov Victor , Margarit Andrei 
Published: October 2018

Summary
Currently, many fields in Russia are at the final development stage known not only for a decreasing percentage of active recoverable reserves, but also for a growing share of hard-to-recover reserves, confined, for example, to complex reservoirs featuring primarily highly zonal and layered heterogeneity. In this context, the priority issue is to spot areas containing remaining reserves with a view to subsequently recovering them. Obviously, this issue cannot be tackled without the aid of advanced technologies of crosswell formation evaluation.
This publication presents the remaining reserves detection technology involving integrated multi-well diagnostics and reservoir flow model (RFM) [1] calibration techniques focused on refining development targets and shaping an appropriate RFM to come up with an action plan to tap reserves and ramp up production at the Company's current assets.
Digitization of Petrographic Data for Standardization and Genetic Interpretation
Authors: Bukharev Aleksandr , Zhukovskaia Elena , Budennyy Semen , Lokhanova Olga 
Published: October 2018

Resume
The article describes the methodology of digital analysis of terrigenous rocks from petrographic images obtained with the help of an optical microscope. The developed methodology is aimed primarily for automatic analysis of the structure, composition of rock-forming components and pore space, but also allows evaluating the type and composition of cement, autigenic minerals.
The result of proposed analysis is a standardized set of quantitative characteristics, which includes the linear dimensions of each grain and distribution parameters (kurtosis, asymmetry, dispersion, sorting, modal, median and maximum values), shape characteristics (area, roundness), grain - texture packing parameters of the sample (linear and area density, contact, morphology of contacts, orientation of minerals, uniformity of packaging, uniformity of distribution). The set of characteristics also includes information about the pore space: the total pore area, hydraulic coefficient, average pore size and connectivity, the shares of intra-and intergranular pore space are additionally calculated. In addition, the set of quantitative characteristics is supplemented by the result of classification of individual rock-forming minerals by composition and secondary changes, and the classification by mineral composition is carried out for autigenic minerals.
The methodology and the result of calculation of these characteristics in this work are demonstrated by the example of a test sample (from the reservoir rock). Petrographic analysis was carried out for this sample in advance and digital pictures were taken with the help of an optical microscope.
Automation and digitalization of such analysis became possible only in conditions when the following problems are solved: computer vision problem (segmentation of individual minerals, classification of their composition and secondary changes based on images taken under an optical microscope), computational geometry problem (calculation of numerical characteristics given above, based on binarized images of “masks" of individual pores and minerals).
Application of Machine Learning Technologies for Rapid 3D Modelling of Inflow to the Well in the Development System
Authors: Simonov Maksim , Akhmetov Alexey , Temirchev Pavel , Koroteev Dmitry , Kostoev Ruslan , Burnaev Evgeny , Oseledets Ivan 
Published: October 2018

Abstract
The most convenient and physically justified tool for optimization of oil field development system is 3D hydrodynamical modeling. The high resource consumption of the method, however, does not allow carrying out fast multivariate calculations. In this paper, we propose an approach to 3D modeling in a development unit, based on the machine learning algorithms. According to available data of the reservoir properties and using high-performance computing systems, we've created a training set and a metamodel of the development unit. Forecasting in the latent variables space makes it possible to perform the necessary calculations many times faster than for the classical approach. We also offer a method for improving the quality of calculations on coarsened grids, that allows to greatly increase the size of training set and to reduce the complexity of setting up a metamodel.
Experience with Using Data Analysis Technologies in Identification of Lost Production Zones
Authors: Nadezhdin Oleg Vladimirovich , Efimov Dmitrii Vital'evich , Minikeeva Lyaysyan Rishatovna , Markov Alexandr Vadimovich 
Published: October 2018

Abstract
Recent reserves depletion and increasing complexity of methods of development efficiency improvement and production stimulation requires solving the problem of "lost sections" of oil-saturated reservoirs. One of the approaches of lost production section search is based on comprehensive analysis of well logging and core data and automation of multi-well analysis of this data. In this case the process of search of lost sections includes both stages of well logging and core data interpretation (including initial work) and analysis of data interpretation results and rating of candidate wells for geological and engineering operations. During initial work and well logging interpretation, specialist has to perform routine tasks that take significant time. For example, such tasks include: initial unification of well logging and core data, depth matching of well logs (single- an multi-type), calibration and splicing of well logs, depth matching of well logging and core data, self-consistent with well logging and core data adaptation of parameters of petrophysical functions and interpretation models, determination of stable correlation "core-log" relationship for complex reservoirs, etc. Most of the tasks listed above involve data analysis. This paper reviews how to automate performance of routine tasks arising during lost section search.
Widely used technologies of data analysis (Data Mining), that are first of all related to tasks of optimization, relationship determination, pattern identification and classification, are to some extent applied during geological modelling. For instance, artificial neural networks, decision trees, Bayesian networks, genetic algorithms, etc. can be used for analysis of geological and geophysical information. Statistical methods such as correlation and regression analysis are often referred to data analysis methods and are applied as well to geological and geophysical information analysis. However, specific research area set its own limits and requirements on the use of tools related to Data Mining.
These are the examples of problems causing unsatisfactory outcome when direct using of Data Mining tool and technologies: –the data does not correlate with each other (in terms of depth), i.e. it is necessary to perform depth matching before data analysis;–training set is inconsistent;–inverse or optimization problem does not have unique solution.
The article discusses the problem of application of data analysis methods and tools to geological and geophysical tasks under presence of uncertainties. Methods of preparing and pre-processing of well data at various stages are presented.
There are introduced the results of using algorithms of data processing and methods of data analysis developed and adapted for particular application tasks.
The Results of Deming Cycle Concept Implementation into Oil Production Processes
Authors: Frolov Sergey , Ermolovich Igor 
Published: October 2018

Abstract
The work analyzes the results of the implementation of the Production Management System (hereinafter System), based on the concept of the Deming Cycle. The system allows automatic selection of Well Interventions, integrated planning of production activities, as well as calculate the production forecast using an integrated field model.
The system uses Big Data technologies, optimization algorithms for various target functions, machine learning methods. The system implements automation of typical tasks, solved by such specialists as geologist, production technologist, reservoir engineers, economist, risk manager. This allows to issue effective recommendations for various production activities on the asset. These recommendations pass the stage of approval by real experts of the Company, after which, based on optimization algorithms, an integrated plan of operational activities is formed. Based on the received integrated plan, the production profile is calculated taking into account interference effects from each of the activities. Then the fact of the planned activities is monitored, on the basis of which the expert system is self-learning in order to improve the accuracy of planning in future.
A significant number and not always satisfactory quality of the data required for the operation of the System, available at the Company, led to the need to develop additional algorithms that are able to work in the case of a limited amount of data. The results of the work in this case require a deeper analysis by field specialists before making a decision. To understand the reliability of the results obtained, the Risk parameter was introduced into the System, which clearly demonstrates which of the recommendations are based on less reliable data and use less accurate methods for evaluating the effects from the activity.
Thanks to the implementation of the Production Management System, significant results have been achieved in terms of reducing bottlenecks and optimizing operating costs. In particular, due to better integrated planning with regard to the selection of measures, taking into account their compatibility, the shortfalls were reduced by more than 10%. By improving the quality of monitoring the effectiveness of planned activities and the corresponding automatic System self-learning, it was possible to achieve a reduction in operating costs by more than 2%.
Applications of Artificial Neural Networks in Gas Injection
Authors: Chu Hongyang , Liao Xinwei , Zhang Wenlong , Li Jinlong , Zou Jiandong , Dong Peng , Liu Wenyuan , Zhao Chaojie 
Published: October 2018

Abstract
Because the ANN model has the ability to fit the data of the complex nonlinear, a large number of field data about gas flooding are collected to train the ANN. Using the formulas, we translate the weighting matrix of ANN which possesses good fitting precision to the weight of single factors for fuzzy mathematic. Then, the fuzzy mathematic method is used to implement comprehensive evaluation to quantized indicators.
The new screening methodology could determine exactly the potential of gas flooding in candidate reservoirs. To overcome the slow convergence of ANN and easy trapping in the local minimum, a large number of field data about gas flooding are collected to train the ANN. Results indicate that the ANN is reliable, and it's mean-square error(MSE) is smaller than 0.01. The weight coefficients of those indicators for fuzzy mathematic are calculated with ANN. The results are as follows: the oil viscosity is the highest score (its weight coefficient is 0.3), followed by the reservoir thickness, reservoir pressure, and reservoir permeability. Moreover, others indicators play a relatively small role. By using the above screening methodology, seven field cases from Ordos Basin are used to evaluate the potential of gas flooding. Results from the field application, indicate that the recovery factors of gas flooding in the field cases are sequential consistency with those from our methodology.
Reservoir Properties Distribution Based on Petroelastic Modeling PEM
Authors: Churanova Nina Yurevna , Chorniy Aleksei Vadimovich , Baranov Timofei Sergeevich , Solovyev Alexey Vitalevich , Sadreev Ernest Anvarovich , Kurelenkov Sergey Khalimovich , Yudin Evgenii Viktorovich , Danko Dmitry Anatolievich 
Published: October 2018

Abstract
The main uncertainty for building 3D geologic and process models is distribution of properties in the inter-well space. The fields comprised of carbonate reservoirs are characterized by the complex porous space structure: availability of secondary porosity, cavern or fracture components. The objective of this paper is to increase the accuracy of the prediction of lithology and permeability and porosity of complex carbonate reservoirs applying the method of petroelastic modelling using the example of one of the Central Khoreyver Uplift (CKU) fields. Obtaining 3D geological and process models capable of quality implementation of representation of the fields’ geological peculiarities is necessary for the purpose of the development tasks: decreasing the uncertainties and reducing the development drilling risks.
The paper proposes a method for predicting reservoir properties of carbonate deposits of Famennian strata of Timano-Pechora petroleum province on the basis of petroelastic modelling. The basis of the method is the principle of complexing different scale geological and geophysical surveys. The lithological division of rocks and identification of reservoir types were performed for the reviewed carbonate deposits. The detailed volumetric lithological and petrophysical models with subsequent tying the obtained results with the core material lithological survey data were developed under results of the complex well logging survey interpretations. An efficient environment model was selected for the reviewed carbonate deposits and petroelastic modelling was carried out. The criteria for predicting the reservoir properties using the seismic data with application of the amplitude inversion method were formulated under results of the petroelastic connections analysis.