What is the one idea you would like the members to take away from this lecture?

Various Enhanced Oil Recovery (EOR) methods have been used to increase oil production and reserves. However, implementing such projects is challenging owing to the higher complexity and larger uncertainty of EOR projects compared with conventional water flooding.

To implement EOR technologies, first, the portfolio of the company should be screened for applicability of the various EOR methods. Next, an appropriate field needs to be chosen for pilot testing of the selected technology. Laboratory experiments are required to determine ranges for the injected EOR fluid properties and fluid-rock-interaction. Pilot testing leads to reducing the subsurface uncertainties but also improves the operating capabilities of the company and economic understanding of EOR projects.

At the example of a polymer EOR project, it is shown that within the last years, significant improvements in predicting polymer EOR performance have been achieved. Injectivity can be assessed using coupled geomechanical-fluid flow models and polymer injection incremental oil recovery can be simulated and optimized taking uncertainty into account. Also, pilot interpretation was advanced by applying the latest tracer technology for reservoir characterisation and monitoring.

In addition to the subsurface assessment, a more holistic view on EOR pilot projects including surface challenges is required to ensure conclusive pilot test results to either implement or drop EOR full-field implementation. A long-term commitment is needed for EOR implementation as well as seamless cooperation between staff operating pilot tests and staff involved in pilot test interpretation.


Dr. Torsten Clemens is a Senior Reservoir Engineering Adviser with OMV Upstream. He used to work in Shell on EOR projects and fractured reservoirs and joined OMV in 2005. In OMV, he is covering EOR/IOR as well as fractured reservoirs and uncertainty management. Torsten published more than 70 technical papers, is a member of various conference committees (SPE, EAGE, WPC), technical editor of several journals and is chairing the IEA EOR Technology Cooperation Program.

This paper discusses the integrated interpretation of PLT data collected in horizontal production (injection) wells with low flow rates and non-uniform inflow (injection) profiles. A factor analysis is performed and normativity of these methods in horizontal wells is defined.


Unlike vertical wells, production logging tool (PLT) techniques (even if adapted to specific conditions) turn to be inefficient in horizontal wells because of stratified flow in case of multiphase (water-oil-gas) fluid and the influence of wellbore trajectory features; this inefficiency is especially obvious in medium- and low-rate wells. It is believed that obtaining accurate and reliable phase profiles in a considerable number of horizontal wells using PLT techniques is very problematic.

Besides, it is only in rare occasions that one of the most important tasks of the PLT survey, which is finding the source of water inflow/breakthrough, can be solved in a horizontal oil well with non-uniform flow profile, even as a mater of quality. Keeping this in mind, gas breakthroughs due to significant negative throttle factor are more reliably identified both by non-stationary temperature logging records and a number of other well logging methods (e.g. SNL, spectral noise logging).

Under these conditions, efficiency of one of the main logging methods – well flow (spinner) measurement – becomes very low. However, alternative geophysical methods (first of all, temperature and water holdup logging) offer a number of additional opportunities. To implement them, the logging technology should include monitoring of well startup and drive change periods. To this end, the logging technology should be designed to allow a series of multi-temporal measurements during these periods.

The role of well testing is to diagnose the flow patterns that are not typical for a classical horizontal well model and estimated reservoir permeability.

Thus, in case of non-uniform low-rate inflow most of the useful information can be obtained by such methods as temperature logging, well testing and partly wellbore fluid analysis methods, which allows to:

  • diagnose phase structure of contrasting liquid and gas inflows based on dynamics of wellbore filling in time;
  • make assumptions on the flow rate of the predominant component based on the form, magnitude and character of temporal changes in behavior of temperature anomalies in intervals outside the working zones;
  • determine reservoir permeability based on well test results and information about the inflow profile.

Thus, a comprehensive interpretation of results of the above mentioned methods allows us to make quite an accurate assessment of the inflow profile and working zones of the reservoir. On the basis of this information we can optimize regimes of the well and reduce the water inflow and gas breakthrough risks.



Melnikov Sergey Igorevich - Ph.D., Head of International Projects Support Department, Gazprom Neft Scientific and Technical Centre. He has been working in the STC since 2010, specializing in the tasks of integrated monitoring of field development. He supervised surveys on new projects of the Company, including in Eastern Siberia and offshore projects, as well as foreign assets. He is currently heading the department that provides geological support for the Company's foreign assets. In 2015, Sergey got PhD degree in Geophysics. He is the author of more than 30 papers.

Kremenetskiy Mihail Izrailevich. Higher Engineering Education (diploma with distinction) Russian State Oil and Gas University

Doctor of Engineering Science, Professor. Author of more than 170 papers, including monographs, patents for inventions, and two recently published books on the theory and practice of production logging and well-test. Works in the oil and gas industry since 1973, since 2000 research and analytical department specialist of the Sibneft company, since 2008 – expert LLC «GAZPROMNEFT SCIENCE & TECHNOLOGY CENTRE».


 The presentation describes main stages of implementation of multilateral drilling in Gazprom neft projects:
  • analysis geological prerequisites;
  • assessment of main value drivers and expected value;
  • organization of pilot works;
  • development drilling.


Oleg Ushmaev, Head of Geology, Gazpromneft Development.

Dmitry Bazhenov, Chief Geologist Gazpromneft Yamal.

Evgeny Zagrebelnyy, Chief Geologist Gazpromneft Badra.

Denis Sugaipov – Gazprom neft Major Projects Director.

Big data analytics has become quite the buzzword in recent years, and its growing application in E&P operations promises to be an exciting new development. It involves: (1) acquiring and managing data in large volumes, of different varieties, and at high velocities, and (2) using statistical techniques to “mine” the data and discover hidden patterns of association and relationships in large, complex, multivariate datasets. The ultimate goal is to extract as much intelligence from our ever-expanding trove of data to improve operational efficiencies and make better decisions for optimizing the performance of petroleum reservoirs. However, the subject remains a mystery to most petroleum engineers and geoscientists because of the statistics-heavy jargon and the use of complex algorithms.
This talk will provide a “gentle” introduction to big data analytics by focusing on: (a) easy-to-understand descriptions of the commonly-used concepts and techniques, (b) broad categories of E&P problems that can be solved with big data analytics, and (c) case studies demonstrating practical applications. The first example to be discussed involves building robust predictive models for oil production in an unconventional reservoir using well architecture and completion data as predictors. The second example involves the ability to predict the presence or absence of vugular zones in carbonate reservoirs based only on a standard suite of electric logs. The third example involves building a data-driven model from historical injection-production data in waterflooding operations for optimization of injection rates and locations. The focus of the talk will be on showcasing an expanded repertoire of statistical and machine learning techniques that can help develop data-driven insights for understanding and optimizing the performance of petroleum reservoirs. 
Dr. Srikanta Mishra is Institute Fellow and Chief Scientist (Energy) at Battelle Memorial Institute. He is responsible for developing and managing a geoscienceoriented technology portfolio related to computational modeling and data analytics for geological carbon storage, shale gas development and improved oil recovery projects. He is the author of a forthcoming book on statistical modeling and data analytics for the petroleum geosciences to be published by Elsevier. He holds a PhD degree from Stanford University, an MS degree from University of Texas and a BTech degree from Indian School of Mines – all in Petroleum Engineering.

Acidizing of a well requires careful optimization. However, the number of laboratory experiments on core dissolution is typically limited by the number of available cores. Thereby, for acidizing optimization reactive fluid flow simulation is frequently applied. Most of the available simulators use as an input a number of empirical coefficients and the choice of their values significantly affects the outcome of the simulation. Better understanding of acidizing process at pore scale can assist in selecting appropriate values for these coefficients.

Recently, we developed a pore-scale image based direct reactive flow modeling approach. This approach is based on a combination of the principles of chemical kinetics/thermodynamics and the density functional theory applied for hydrodynamics (DFH). DFH proved itself to be very effective for pore-scale modelling of multiphase flow regarding its ability to handle complex physical phenomena. Chemical reactions are introduced to hydrodynamic simulation within the framework of a partial local equilibrium assumption.

In the current study, it is demonstrated that developed approach adequately describes dissolution of dolomite rock by solution of hydrochloric acid. Simulations have been performed using 2D model of dolomite granule, 2D model of porous structure and 3D model of Silurian dolomite microstructure. Upon acid injection, the geometry of a rock is gradually changing along the path of acid penetration. The modeling results reveal the dependence of dolomite dissolution rate on the rate of fluid injection. Using the developed approach, it was also demonstrated that release of gaseous CO2 influences the rate of mineral dissolution. The correlations obtained from reactive fluid flow with exact geometry can be utilized for amendment of the reaction rate constants which are used for large scale simulations.

The suggested approach for reactive fluid flow simulation allows to test numerous “what if” scenarios and to evaluate the effect of different factors on mineral dissolution rate at pore scale. It paves the way for increasing the consistency between the models used for reactive flow modeling and pore scale heterogeneity of real rocks, which will lead to improvements in acidizing job design.

About author:

Beletskaya Anna


Anna graduated from Chemistry Department of the Lomonosov Moscow State University (Moscow, Russia) in 2010. In 2013 she got PhD degree in Chemistry from the same institution. Since 2007 to 2013 she worked as an engineer in Moscow State University and contributed into multiple research projects devoted to the investigation of catalytic reactions mechanisms and establishment of structure-property relationship using quantum chemical simulations.  

In 2014 Anna joined Schlumberger Moscow Research as a Research Scientist. Her current research activity is focused on pore scale simulations of minerals dissolution.



Cost-engineering waterflooding management methods and tools for West Siberian oil fields


OPEX optimization of the oil field development system in Western Siberia is the important task for oil companies. This is due to both a decline in oil prices and the watercut growth in the production. Companies are forced to have large costs associated with organizing the injection of the working agent of the water flooding system, lifting the liquid to the surface, and working on fluid dehydration. Often, the total value of operating costs forces companies to abandon some production wells, which negatively affects both the Company's income and the level of recovery factor.


The development of simulation modeling tools opens up opportunities for companies to optimize key technological and economic indicators of field development. This is especially useful for old fields at the final stage of development, the achievement of profitability of which is impossible without continuous optimization measures.


However, the geological uncertainties and the complexity of the evaluation of the hydrodynamic connection between the injection and production wells do not allow oil companies to obtain a correct answer to the question of the efficiency of the current water flooding system and individual injection wells. Unfortunately, the complexity of creating a permanent hydrodynamic model, connected both with the unreliability of input data, and with high labor and computational costs does not allow to fully meet the requirements for optimizing the waterflooding system. At the same time, analytical methods, despite their simplicity and flexibility, are not popular due to low predictive ability


In this connection, the greatest attention is paid to the hybrid hydrodynamic model based on the capacitive-resistive analogy (CR). The use of this model is based on training on historical data, testing the quality of training on test historical data and subsequently forecasting development indicators. Based on physical processes, a simplified model of material balance with a minimum number of unknowns makes it possible to identify efficiently and with sufficient quality injection wells with a low production effect and predict the effect of injection rate change. In integration with the economic model, this CR-method allows to forecast and maximize NPV depending on the Company’s variable costs.


Particular attention is paid to the aspects of block analysis (BFA): predicting watercut based on displacement characteristics, factor analysis of changes in oil production and cash flow.


The use of the method at a number of fields in Western Siberia has demonstrated good convergence with the results of calculations on more complex numerical models.

About author:



Mikhail Naugolnov – reservoir engineering manager in LLC Gazpromneft STC. In 2011 he graduated with honors St. Petersburg Mining Institute, specializing in the petroleum engineering, in 2012 - with honors in economics and management. In 2011-2012 he worked for Total E&P Russie in the project of commissioning the Kharyaga oil field. Since 2013, he has been working at LLC Gazpromneft STC, in direction related to reservoir engineering, design, monitoring, development management, simulation modeling, and automation of calculation methods. Author more than 20 scientific works.



The presentation is divided into two parts. In the first one, the speaker will present a general view on modern approaches of big data processing (using machine learning methods) in application for oil and gas industry. Some myths related to BIG DATA approaches, barriers of their implementation within the industry will be presented as well as the idea why in some industries data science instruments are fruitful while in others are not. The second part will be devoted to application of spectral methods and deep learning algorithms for thin sections analysis of sandstones. It will be demonstrated how these methods allow us to reduce significantly time wasting for routing processes as well as to enhance the data value .



Semeon BUDENNYY, Head of Department of Digital Technologies in the Industry at the Center for Engineering and Technology of MIPT (CET MIPT), PhD student at MIPT. In 2014 he obtained the Master’s degree in Physics at NSU, in 2011 – Bachelor’s degree in Physics at NSU, in 2007 he graduated from Specialized Educational Scientific Center of NSU. He has been working at CET-MIPT from 2014, being an SPE member from 2014.


Drilling groups and executives generally have a different view of measuring drilling performance. To executives, “Drilling” commonly refers to all aspects of well construction, including drilling, completions, hook-up, procurement, the asset team, and other groups. Good measures of performance can drive improvements between these groups. The first key to success is how to communicate drilling performance in terms that answer the questions of executives and managers, which requires a business-focused cross-functional process. The second key to success is to drive operational performance improvement, which requires a different set of measures with sufficient granularity to define actions. Over the past 10 years, a very workable system has evolved through various approaches used in drilling more than 16,000 wells in the US, South America, and the Middle East. The system has delivered best-in-class performance. It has proven that an effective performance measurement system which addresses both executive requirements and operational requirements can both deliver outstanding results, and also communicate those results, with remarkable value to the organization.  


John Willis is New Mexico Drilling and Completions Manager for Occidental Oil & Gas Corporation. His responsibilities include all aspects of drilling, fracturing, and completing unconvetional horizonal wells. Prior to this role, he was Chief of Drilling, with responsibility for standards, operational support, global systems, the drilling data system, and tools for drilling performance measurement. Prior to his Chief role, he served as Drilling Manager in Oman and Drilling Manager in Libya. His experience prior to Oxy includes other drilling roles, service company roles related to project management and software development, and he operated a consulting and software business. He has Chaired two SPE Forums, served on Forum Steering Committees, and Chaired the 2003 SPE/IADC Drilling Conference.

Mathematical modeling of phase behavior of multicomponent hydrocarbon mixtures is an essential part of up-to-date practices in petroleum reservoir engineering. Phase behavior calculations form the basis of the PVT software, as well as the 'flash' procedures for determination of phase state and compositions within compositional flow simulators. Adequate description of phase behavior is important for simulation of petroleum production with intensive phase transitions in the reservoir, wells and surface facilities.

One of the key assumptions of industry adopted models is that phase state of the hydrocarbon mixture and phase compositions correspond to the condition of thermodynamic equilibrium. However, there are typical cases for oil and gas-condensate reservoirs when field data are principally inconsistent with equilibrium models. Some examples to give are data of well operation at Novogodneye, Vuktylskoye, Krasnoleninskoye, Kamennoye and many other fields.

In hydrocarbon production, non-equilibrium effects are evident in the following cases:

1) pressure increase in a reservoir (by water or gas injection) following previous pressure depletion with evaluation of the second hydrocarbon phase (liberation of dissolved gas from oil or retrograde condensation in a gas-condensate system) – so-called gas dissolution / condensate evaporation hysteresis;

2) pressure depletion in a gas-condensate reservoir below the maximum condensation pressure (transition from retrograde condensation to direct re-vaporization);

3) gas injection in oil or gas-condensate reservoir.

Similar processes may also take place during hydrocarbon flow in wellbores and surface facilities.

Non-equilibrium effects result in considerable (tens or hundreds percent) deviation of actual reservoir system parameters (saturation pressure, production composition) from their estimates by equilibrium models.

For practical needs, reservoir engineers are limited to either using equilibrium compositional models with no account for non-equilibrium effects, or black oil models with the option of limited gas dissolution /condensate vaporization/ This option is based on a simple technical relation and doesn't consider specific physics of non-equilibrium processes.

In the presentation, methods and algorithms are presented for non-equilibrium phase behavior simulations suitable for wide practical use. A relation is shown between non-equilibrium effects and simulation scale. As the applications, flow simulations with compositional and black oil formulations are considered. Phase behavior simulation cases are shown for real oil and gas-condensate mixtures, including matching of the non-equilibrium condensate recovery dynamics for the late stage of production at the Vuktylskoye field.


Ilya M. Indrupskiy

Chief researcher / head of Gas-, Oil- and Condensate Recovery Lab of the Oil and Gas Research Institute of the Russian Academy of Sciences (OGRI RAS). Professor of the Applied Mathematics and Computer Modeling Department of the Gubkin State University of Oil and Gas.

Graduated from the Gubkin University with an engineering degree in applied mathematics. Doctor of technical sciences in reservoir engineering. Professor of the Russian Academy of Sciences. Author of more than 150 journal and conference papers and more than 20 patents.

Research area includes improvement of integrated 3D reservoir modeling; forward and inverse problems of fluid flow and thermodynamics in oil and gas reservoirs; development of highly informative well testing and data interpretation methods; advancements in production techniques for hard-to-recover hydrocarbons.

Ilya has a considerable experience in research projects for the Russian Academy of Sciences, as well as for Gazprom Neft, TNK-BP, Rosneft, Lukoil, Gazprom and other companies.

Reliable information about reservoir properties and its variation within the reservoir is a key factor in reducing uncertainty within the choice of an asset development strategy, technological solutions, estimation of recoverable reserves and feasibility of development strategies. In case of waterflood designing or other methods of pressure maintenance for inhomogeneous, anisotropic collector, among necessary initial parameters we need the most accurate data on displacement efficiency, relative phase permeability functions, permeability values ​​along lateral and vertical coordinates, and principal directions of permeability tensor for complex carbonate objects. All those characteristics are currently determined from data of laboratory core studies, with total impossibility to transfer it correctly to the scale and conditions of fluid flow in formation during field development.

For 15 years the authors have been developing new methods and technologies for complex well testing. For each type of research, a specially planned sequence of technological operations, extended complex of hydrodynamic, geophysical measurements and methods production logging provide highly informative data on multidimensional multiphase filtration processes directly at reservoir conditions.

To determine desired reservoir characteristics, obtained data are interpreted by data assimilation within inverse problem solution. Corresponding forward problems are solved in transient, multiphase and / or multidimensional statement, with full consideration for object peculiarities (heterogeneity and anisotropy of formation properties, compressibility of fluids and rocks, possibility of separating dissolved gas, variable mineralization of water, etc.). Solution of corresponding inverse problems is carried out using effective optimization methods and methods of optimal control theory (adjoint method). Algorithms and software have been developed for numerical solution of forward and inverse problems.

A series of patents has been obtained for new methods of well testing and related technical solutions. Technologies are tested on a number of domestic deposits. Substantial results are obtained, new interesting effects are revealed.

Our presentation will highlight the main ideas, achieved results and accumulated experience, with an emphasis on the scientific component of topic considered.


S.N. Zakirov, E.S. Zakirov, I.M. Indrupsky, 
D.P. Anikeev, T.N. Tsagan-Mandjiev, M.N. Baganova, OGRI RAS


Ernest S. Zakirov


Professional Characteristic

Doctor of Technical Sciences, Professor of the Russian Academy of Sciences E.S. Zakirov is a leading scientist in the field of modeling oil and gas fields development, development optimization of natural hydrocarbon deposits, history matching of 3D hydrodynamic models, specialized well testing, and an expert in domestic oil and gas projects.

E.S. Zakirov already has published over 225 scientific works, including 7 monographs and 1 book, possesses more than 40 patents for inventions, including international (USA). Prepared 5 candidates of sciences. He is also SPE member.



In 1991 he graduated cum laude from Moscow State University named after M.V. Lomonosov.

In 1991-1994 years – post-graduate student of Moscow State University named after M.V. Lomonosov.

In 1997 he defended his candidate degree.

In 2001 he defended his doctoral dissertation.

In 2015, he was elected professor of the Russian Academy of Sciences by the Department of Earth Sciences of the Russian Academy of Sciences.


Professional activity

1994 to present time

Principal Researcher of the Gas-Oil-Condensate Recovery Laboratory of Oil and Gas Research Institute of Russian Academy of Sciences.

Creates new and improves existing technologies for oil and gas fields development.

Along with fundamental research, he is engaged in designing and improving development of oil and gas fields, including Yaro-Yakhinskoye, Western Siberia (1997), Severo-Vasyuganskoye, Tomsk Region (1998), Talinskoe field, Western Siberia (2000), Pribrezhnoye field (2001), Prirazlomnoye, the Barents Sea (2002), the Novogodnee. West Siberia (2006).

Since 1991, he has been conducting joint scientific research with Statoil, Norsk Hydro, Verbundnetz Gas, YUKOS, SIDANKO, Lukoil, Rosneft, TNK-BP and other companies.