In the current oil and gas environment, operators have focused on production optimization, effectively squeezing every last drop of oil out of their wells. Autonomous Inflow Control Device (AICD) technology has been deployed as part of the completion in old and new wells resulting in increased oil production by reducing water and gas production. For many years, inflow control devices (ICD), which restrict flow by creating additional pressure, have been used to mitigate this problem. They are however, passive in nature and after the onset of water or gas breakthrough, the choke effect cannot be adjusted without intervention.

The AICD is an active inflow control device with a self-adjustable design to self-regulate and provide greater choke when an unfavorable fluid such as gas and water ingress. This prevents the well from being flooded when unwanted fluids breakthrough, therefore providing the advantage of being able to even out the inflow into well. In addition, it will also choke the unfavorable breakthrough sections of the well and producing from remaining sections leading to greater recovery, lower water, and gas production.

This technology has helped improve recovery in horizontal well across the globe by reducing gas-oil ratio or water cut of the well, thus increasing ultimate oil recovery. The key factor to successful application is a systematic approach in prediction modeling and well design workflow to select a well candidate between Passive and Autonomous inflow control device.

Link for presnetaiton download:  

About Author:


Dr. Ismarullizam Mohd Ismail is the Subsurface Engineering Manager for Tendeka based in Aberdeen, United Kingdom. He received a MSc. and Ph.D. in Mechanical Engineering from the University of Leeds, United Kingdom. He has been working in sand control and inflow control technology for over 15 years in multiple roles, mainly in offshore operation, project engineering and product development. His current work involves developing new inflow control technology, subsurface modeling and managing an inflow control product line. He has designed and modeled AICD/ICD nozzle completions for more than 100 wells across the globe and he also holds various patents for inflow control design. Prior to joining Tendeka, Dr Mohd Ismail worked for various major service companies and carried out university research.

Tuesday, 05 February 2019

New approaches to the study of wells

Currently, the methods of marker (tracer) diagnostics, which allow obtaining qualitative and quantitative data on the operation of well intervals without performing downhole operations, are becoming more common in the world. The principal difference between these technologies and traditional well logging methods (GIS) is the ability to monitor the operation of multiple hydraulic fracturing or well intervals over a long period of time with a significant decrease in the resources involved, a reduction in costs and an increase in production safety.

Well studies using marker technologies can improve the efficiency of diagnostics of inflows in wells when developing oil and gas fields and solve a number of important tasks, such as: ∙ evaluation of the well flow profile after the multi-stage hydraulic fracturing; ∙ evaluation of the performance of each step in water and oil; ∙ optimization of technical solutions for well completion in the early stages of field development; ∙ analysis of potential long-term fluid recovery; ∙ obtaining detailed information for analyzing the mutual influence of neighboring wells; ∙ obtaining information on the dynamics of production of the oil reservoir area.

Also, in addition to an alternative GIS method, technologies for marking downhole equipment can be used for flow measurement data in the WEM layouts and in monitoring the integrity of the packers. The key topic of the report is the methodology for integrated assessment of the efficiency, reliability and accuracy of work for various marker technologies available on the market. Often, oil and gas companies decide on the use of marker technologies without any testing or testing, based only on the reputation of the supplier, the duration of its presence in the market or value. The reason for this may be the lack of standardized test methods, as well as experience in sharing best practices between subsoil users. At the same time, marker technologies are a relatively new field of activity in the field of well studies, therefore, it is necessary to approach the assessment of technologies on the basis of objective indicators.The report presents the results and methodology of testing various marker technologies that can be used as technical criteria when choosing a contractor for marker research.




About Author:

Ovchinnikov Kirill Nikolayevich has extensive experience in the field of downhole operations, coiled tubing services, hydraulic fracturing and oilfield service equipment He is an expert in the field of safety and quality of field operations, standardization of business processes and implementation of quality management systems.

He has many years of industrial experience in leading international service and mining companies in Saudi Arabia, the United Arab Emirates, Kuwait, Egypt, Australia and Russia. MBA with a degree in Management in the Oil and Gas Industry (Curtin University, Australia) and a master’s degree at the RSUGU. Gubkin specialty "Oil and gas business." Member of the Program Committee of the Russian Oil and Gas Technical Conference SPE (Society of Petroleum Engineers), member of the Eurasian Union of Subsoil Use Experts (ESAS).



Hydrocarbons in oil fields are affected by various secondary processes, such as biodegradation, migration of deep-seated gas, movement of formation water, and evaporation. The degree of hydrocarbon changes depends on many factors: reservoir temperature, tectonic activity, dissection of productive strata, activity of water-bearing horizons, etc. In this connection, oil initially migrated from one source rock varies differentially in different reservoirs and parts of deposits. Using high-resolution gas chromatography, it is possible to identify differences between oil samples from different formations and formation sections. Assessing the degree of secondary changes allows you to identify oils of various reservoirs, in other words, to determine the unique appearance of oils - “oil fingerprints” or otherwise the final members. Having a set of unique “oil fingerprints” - the end members representing the reservoirs being developed, it becomes possible to determine the contribution of individual reservoirs to the production of mixed products. This information can be very valuable both for solving current development management tasks and optimizing a long-term oil field development strategy. This paper presents the results of a pilot project on the introduction of geochemical analysis of oil using oil fingerprinting technology based on high-resolution gas chromatography into the development management process of the Astokhsky section of the Piltun-Astokhsky oil and gas condensate field. operating several layers with the subsequent practical implementation in production. In the course of work, the broader possibilities of the method were also identified, namely, monitoring of interfacial flows, clarification of the geological structure of the field, identification of leaks in production wells.


Dmitry Pavlov in 1999, he graduated from Kazan State University with a degree in Geology of Oil and Gas. In 1999 - 2004 he worked in a number of service companies in the oil and gas sector. He was engaged in geological and hydrodynamic modeling of oil fields in the Ural-Volga region and Western Siberia. In 2005 he worked as a development engineer in the service company TGT Oil & Gas Service. He was engaged in research of optimization of the waterflooding scheme of the Lehvayr oil field (Sultanate of Oman). In 2005-2007 Worked as Lead Development Engineer at TNK-BP Management. He was engaged in the optimization of waterflooding schemes for the Orenburgneft fields. From 2007 to the present, he has been working as a lead development engineer for Sakhalin Energy Investment Company Ltd. (Sakhalin Energy).  He is responsible for managing the current development, as well as optimizing long-term development plans for the Piltun-Astokhsky oil and gas condensate and Lunsky gas and condensate fields located on the shelf of Sakhalin Island (RF). His area of ​​interest is the development of oil rims, modern methods for monitoring and managing the development of oil and gas condensate fields, improving efficiency and methods for improving the development of offshore fields.


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.