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The results of sedimentological core analysis of the Achimov Formation (Upper Valanginian, Lower Cretaceous) confirm that it was formed by higher efficiency systems of submarine fans in (relatively) deep marine basin. Lithofacies models of Ach5-6 were generated, well correlation was performed based on the comprehensive analysis of core, well logging and seismic data. Distributary channels and proximal parts of depositional lobes are characterized by the best reservoir properties.

During field development of a microgrout for the stabilization of painted lime plasters detached from a limestone substrate, diethyl oxalate-based formulations out-performed microgrouts based on na...

Summary In subsea environments, the use of larger-bore/higher-rate well designs is often a key contributor to the economic recovery of hydrocarbon resources. Their use is a necessity for accommodating the huge production capacity of the reservoirs they penetrate, with the major benefit of minimizing the number of wells necessary to develop a subsea field. The enthusiasm for using such well designs, however, must also be tempered by a clear understanding of the considerable well control risk they introduce - that risk being an increased level of difficulty in bringing such a well under control if a blowout were to occur. It is not uncommon that multiple relief wells would be simultaneously required to bring a big-bore blowout under control. The discussion of this fact is, though, not a common topic in industry literature. Instead, capping stacks have been more the focus. Much recent attention has been trained on ensuring that capping stacks are a viable method for quickly responding to a high-rate subsea blowout. This makes sense in light of the simpler, and publicly more palatable, concept of rapidly installing a capping stack on a blown-out subsea well, relative to the less-desired complexities and significant time investment of drilling relief wells. Still, a capping stack is only as reliable as the wellhead it must connect to. It is because subsea wellheads have such a high chance of being damaged during a blowout that relief wells will always be relied on as the ultimate backstop for ensuring that a subsea blowout can be brought under control. This reliance on relief wells, as they are traditionally envisioned, has limitations though when addressing a high-rate subsea blowout. Any subsea relief well will have inherent limitations resulting from the architecture of choke and kill lines (flow restrictions) and that of the cross-over piping at the BOP (erosion concerns). In the world of high-rate subsea blowouts, these limitations can sometimes translate into multiple relief wells being required to inject fluid at the rates necessary to effect a dynamic kill. But, the simultaneous use of multiple subsea relief wells to dynamically kill a single blowout has only been tried once in the industry's history. As a result, some countries require that stopping a blowout must be possible by drilling only one relief well. This paper describes methods that can be implemented to transcend traditional relief well limitations via the use of a relief well injection spool (RWIS), with the ultimate goal of dynamically killing a subsea big-bore blowout using a single relief well. The technique varies with water depth. In both shallow- (826 ft) and deep-water (8260 ft) environments, techniques are presented and analyzed that will allow using a single subsea relief well to perform a dynamic kill using 15 lbm/gal drilling fluid injected at 238 bbl/min. This particularly severe scenario, based on a big-bore gas well development in Western Australia, is chosen so that our results will have applicability to most sub-sea well control events that might arise in the future.

Fractured crystalline basement reservoirs (basement) on the UK Continental Shelf (UKCS) and the Norwegian Continental Shelf (NCS) have been underexplored. Over the last 12 years, Hurricane Energy has deliberately set out to explore basement potential by exploring and appraising the Rona Ridge, West of Shetland; and the Rona Ridge Lancaster Field is now being progressed towards being the first UK basement field development. The Norwegian basement play is also recognized as a potentially material resource through serendipitous oil discoveries, with the 16/1-15 well, drilled in 2011, being the first successful full-scale basement test on the NCS. Building on this success, the 2018 Rolvsnes appraisal well (16/1-28 S) has demonstrated the significant basement potential of the extensive Utsira High and confirmed the materiality of a Norwegian basement play. The Rona Ridge and Utsira basement discoveries are used as a comparison with two other, yet to be evaluated, prospective basement plays on the NCS, with the objective of establishing technical subject areas where future UKCS and NCS collaboration would aid in accelerating understanding of the UKCS–NCS basement play.

In recent years, China has made certain achievements in shallow sea petroleum geological exploration and development, but the exploration of deep water areas is still in the initial stage, and the water depth in the South China Sea is generally 500 to 2000 meters, which is a deep water operation area. Although China has made some progress in the field of deep-water development of petroleum technology research, but compared with the international advanced countries in marine science and technology, there is a large gap, in the international competition is at a disadvantage, marine research technology and equipment is relatively backward, deep-sea resources exploration and development capacity is insufficient, high-end technology to foreign dependence. In order to better develop China's deep-sea oil and gas resources, it is necessary to strengthen the development of drilling and completion technology in the oil industry drilling engineering. This paper briefly describes the research overview, technical difficulties, design principles and main contents of the completion technology in deepwater drilling and completion engineering. It is expected to have some significance for the development of deepwater oil and gas fields in China.

Данная статья открывает цикл статей, посвященного работе по оптимизации системы разработки коллекторов с низкими фильтрационно-емкостными свойствами на примере Эргинского лицензионного участка. Приведено описание истории развития актива, от первой оценки его потенциала до запуска в промышленную эксплуатацию и постоянной борьбы за рентабельность проекта. Эргинский ЛУ Приобского месторождения приобретён ПАО «НК «Роснефть» в 2017 году. По результатам бурения первых эксплуатационных скважин выяснилось, что первоначальная оценка продуктивности пластов была ошибочной. Для дальнейшей рентабельной разработки ЛУ предложен переход на системы горизонтальных скважин, расположенных поперек направления распространения регионального стресса с увеличением количества стадий гидроразрыва пласта., This article opens a series of articles devoted to the work on optimizing the system of developing collectors with low filtration properties on the example of the Erginsky license area. The article describes the history of the asset's development, from the first assessment of its potential to the launch into commercial operation and the constant struggle for the profitability of the project. Erginsky LA of the Priobskoye field was acquired by oil company “NK “Rosneft” PJSC in 2017. According to the results of drilling the first production wells, it turned out that the initial assessment of reservoir productivity was erroneous. For further cost-effective development of the area, a transition to systems of horizontal wells located across the direction of regional stress propagation with an increase in the number of hydraulic fracturing stages is proposed.

УДК 622.276.344 DOI 10.24412/1728-5283_2022_3_105_113 МЕТОДОЛОГИЯ ОПРЕДЕЛЕНИЯ ПОЛОЖЕНИЯ СТВОЛА ГОРИЗОНТАЛЬНОЙ СКВАЖИНЫ ПО ГЕОЛОГИЧЕСКОМУ РАЗРЕЗУ С УВЕЛИЧЕНИЕМ КОЭФФИЦИЕНТА ОХВАТА © Сайфуллин Аскар Айдарович, Мубаракшин Ленар Наилевич, Пупков Николай Владимирович ООО «Тюменский нефтяной научный центр», Тюмень, Российская Федерация На сегодняшний день с развитием компьютерных технологий сфера нефтегазовой промышленности значительно модернизировалась с середины 20-го века. Многие процессы оптимизированы и автоматизированы, но до сих пор существует область в принятии решения по разработке месторождений, которой необходима трансформация. При выборе положения горизонтального ствола нефтяной скважины по геологическому разрезу основным методом являются многовариантные гидродинамические расчеты. Несмотря на то, что подход получил широкое распространение во многих нефтегазовых компаниях, он обладает рядом недостатков: необходимость больших вычислительных мощностей, расчетного времени, высоких трудозатрат на подготовку и обработку результата, неустойчивости решений в виду невозможности расчета всех возможных вариантов траекторий. В работе рассматривается методика оценки эффективности проводки скважин, основанная на статистике и теории графов, позволяющая устранить ряд недостатков существующего традиционного подхода. Основным принципом методики является анализ статических геологических свойств, которые влияют на объем дренируемых запасов, вовлеченных скважиной и, как следствие, на накопленную добычу за рентабельный период. Разработан алгоритм, определяющий наиболее перспективные для вовлечения в разработку участки пласта при известных координатах точки входа в пласт (Т2) и окончания ствола скважины (Т3), учитывающий технологическую возможность бурения каждого сегмента рассматриваемой траектории. Перспективность зон определяется путем применения разработанной целевой функцией, которая учитывает фильтрационно-емкостные свойства, а также характер насыщения ячеек в геолого-гидродинамической модели. При рассмотрении всех возможных траекторий и расчета целевой функции производится качественное ранжирование скважин. Предложенный в работе подход опробован на гидродинамических моделях нефтяных месторождений Западной и Восточной Сибири, проведено сравнение с результатами многовариантного гидродинамического расчета. Оптимальная траектория характеризуется максимальной добычей нефти и кратным сокращением времени расчета. Разработанный алгоритм представляет из себя комплекс программ-скриптов для распространенных гидродинамических симуляторов с поддержкой языка программирования Python., Today, with the development of computer technology, the oil and gas industry has been significantly modernized since the middle of the 20th century. Many processes have been optimized and automated, but there is still an area in the decision-making on the oil field development that needs transformation. Multiple run simulation is the main method when choosing the position of a horizontal oil well along a geological section. Despite the fact that the approach has become widespread in many oil and gas companies, it has a number of disadvantages: the need for large computing power, estimated time, high labor costs for preparing and processing the result, instability of solutions due to the impossibility of calculating all possible trajectory options. The paper considers a methodology for evaluating the efficiency of well placement based on statistics and graph theory, which allows to eliminate a number of disadvantages of the existing traditional approach. The main principle of the methodology is the analysis of static geological properties that affect the volume of drained reserves involved by the well and, as a result, the accumulated production over a profitable period. An algorithm has been developed that determines the most promising areas of the reservoir for involvement in development at known coordinates of the point of entry into the reservoir (T2) and the end of the borehole (T3), taking into account the technological drilling possibility each segment of the trajectory under consideration. The prospects of the zones are determined by applying the developed objective function, which takes into account the filtration and capacitance properties, as well as the nature of cell saturation in the geological and hydrodynamic model. When considering all possible trajectories and calculating the objective function, a qualitative ranking of wells is performed. The approach proposed in this paper has been tested on hydrodynamic models of oil fields in Western and Eastern Siberia, compared with the results of multivariate hydrodynamic calculation. The optimal trajectory is characterized by maximum oil production and a multiple reduction in the calculation time. The developed algorithm is a set of script programs for common hydrodynamic simulators with support for the Python programming language.

Работа посвящена созданию и апробации инструмента поиска и ранжирования объектов-аналогов из базы данных разработки месторождений на основе теории нечетких множеств. Реализованный функционал позволяет выбирать задачи и целевые параметры, по которым подбираются объекты-аналоги. В алгоритме введены весовые показатели для каждой задачи соответственно, основанные на экспертном мнении и статистике. Результат работы инструмента позволяет воспользоваться существующим опытом разработки схожих объектов из базы данных и восполнить недостающую информацию., The work is devoted to the creation and testing of a tool for searching and ranking objects-analogues from the field development database based on the theory of fuzzy sets. The implemented functionality allows you to select tasks and target parameters, according to which analogous objects are selected. The algorithm introduces weight indicators for each task, respectively, based on expert opinion and statistics. The result of the tool allows you to use the existing experience in developing similar objects from the database and fill in the missing information.

В настоящий момент большую значимость приобретают проблемы оценки разработки нефтегазовых месторождений. При мониторинге реализации стратегии развития нефтяной промышленности используются несколько показателей по направлениям развития отрасли. Так как различные показатели объектов относятся к различным проблемам нефтяной промышленности, подытожить эти данные без специального инструментария становится невозможным. В разработке нефтегазовых месторождений для принятия решений индивидуальные оценки экспертов эффективности не помогут. Это связано с тем, что у специалистов, которые оценивают показатели, разные ожидания. Из чего можно заключить, что данная ситуация является причиной столкновения интересов при рассмотрении разработки месторождений. В этой ситуации возникает потребность получения интегральной оценки. В статье описана предлагаемая модель оценки эффективности разработки месторождения на основе расчета интегрального показателя с использованием экспертных методов. Разработанная модель позволяет повысить эффективность принятия решения при управлении нефтегазовыми месторождениями. Она информирует специалистов нефтегазового дела, имеет ли смысл дальнейшая разработка нефтегазового месторождения. Модель апробирована на примере Северо-Ингольского, Зимнего, Орехово-Ермаковского, им. Александра Жагрина месторождений в ПАО «Газпром нефть», предполагается дальнейшая реализация в виде модуля в системе «Интеграционная система долгосрочного развития»., Nowadays, the problems of assessing the development of oil and gas fields are becoming increasingly important. When monitoring the implementation of the strategy for the development of the oil industry, several indicators are used in the areas of development of the industry. Since different indicators of objects relate to different problems of the oil industry, it appears to be impossible to summarize these data without special tools. In the development of oil and gas fields for decision-making, individual assessments of efficiency experts will not help due to the fact that specialists who evaluate performance have different expectations. Therefore, it can be concluded that such situation is the cause of a conflict of interest when considering the development of deposits. In this situation, there is a need to obtain an integral estimate. The article describes the proposed model for evaluating the efficiency of field development based on the calculation of an integral indicator by means of expert methods. The developed model enables the increase of decision-making efficiency in the management of oil and gas fields. The model was tested on the example of Severo-Ingolsky, Zimny, Orekhovo-Ermakovskoye, Alexander Zhagrin fields in Gazprom Neft, further implementation is expected as a module in the Integration system for long-term development system., МОДЕЛИРОВАНИЕ, ОПТИМИЗАЦИЯ И ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ, Выпуск 2 (37) 2022, Pages 18-19

Although it is possible to apply traditional optimization algorithms to determine the Pareto front of a multi-objective optimization problem, the computational cost is extremely high, when the objective function evaluation requires solving a complex reservoir simulation problem and optimization cannot benefit from adjoint-based gradients. This paper proposes a novel workflow to solve bi-objective optimization problems using the distributed quasi-Newton (DQN) method, which is a well-parallelized and derivative-free optimization (DFO) method. Numerical tests confirm that the DQN method performs efficiently and robustly. The efficiency of the DQN optimizer stems from a distributed computing mechanism which effectively shares the available information discovered in prior iterations. Rather than performing multiple quasi-Newton optimization tasks in isolation, simulation results are shared among distinct DQN optimization tasks or threads. In this paper, the DQN method is applied to the optimization of a weighted average of two objectives, using different weighting factors for different optimization threads. In each iteration, the DQN optimizer generates an ensemble of search points (or simulation cases) in parallel and a set of non-dominated points is updated accordingly. Different DQN optimization threads, which use the same set of simulation results but different weighting factors in their objective functions, converge to different optima of the weighted average objective function. The non-dominated points found in the last iteration form a set of Pareto optimal solutions. Robustness as well as efficiency of the DQN optimizer originates from reliance on a large, shared set of intermediate search points. On the one hand, this set of searching points is (much) smaller than the combined sets needed if all optimizations with different weighting factors would be executed separately; on the other hand, the size of this set produces a high fault tolerance. Even if some simulations fail at a given iteration, DQN’s distributed-parallel information-sharing protocol is designed and implemented such that the optimization process can still proceed to the next iteration. The proposed DQN optimization method is first validated on synthetic examples with analytical objective functions. Then, it is tested on well location optimization problems, by maximizing the oil production and minimizing the water production. Furthermore, the proposed method is benchmarked against a bi-objective implementation of the MADS (Mesh Adaptive Direct Search) method, and the numerical results reinforce the auspicious computational attributes of DQN observed for the test problems. To the best of our knowledge, this is the first time that a well-parallelized and derivative-free DQN optimization method has been developed and tested on bi-objective optimization problems. The methodology proposed can help improve efficiency and robustness in solving complicated bi-objective optimization problems by taking advantage of model-based search optimization algorithms with an effective information-sharing mechanism.

In pursuit of efficient oil and gas field development, including hard-to-recover reserves, the key objective is to develop and provide the rationale for oil recovery improvement recommendations. This paper presents the results of the use of the workflow process for optimized field development at two field clusters of the Yuzhno-Vyintoiskoye field using geological and reservoir modelling and dynamic marker-based flow production surveillance in producing horizontal wells. The target reservoir of the Yuzhno-Vyntoiskoye deposit is represented by a series of wedge-shaped Neocomian sandstones. Sand bodies typically have a complex geological structure, lateral continuity and a complex distribution of reservoir rocks. Reservoir beds are characterised by low thickness and permeability. The pay zone of the section is a highly heterogeneous formation, which is manifested through vertical variability of the lithological type of reservoir rocks, lithological substitutions, and the high clay content of reservoirs. The target reservoir of the Yuzhno-Vyintoiskoye field is marked by an extensive water-oil zone with highly variable water saturation. According to paleogeographic data, the reservoir was formed in shallow marine settings. Sand deposits are represented by regressive cyclites that are typical for the progressing coastal shallow water (Dulkarnaev et al., 2020). Currently, the reservoir is in production increase cycle. That is why an integrated approach is used in this work to provide a further rationale and creation of the starting points of the reservoir pressure maintenance system impact at new drilling fields to improve oil recovery and secure sustainable oil production and the reserve development rate under high uncertainty.

The main technology used to optimize field development is hydrodynamic modeling, which is very costly in terms of computing resources and expert time to configure the model. And in the case of brownfields, the complexity increases exponentially. The paper describes the stages of developing a hybrid geological-physical-mathematical proxy model using machine learning methods, which allows performing multivariate calculations and predicting production including various injection well operating regimes. Based on the calculations, we search for the optimal ratio of injection volume distribution to injection wells under given infrastructural constraints. The approach implemented in this work takes into account many factors (some features of the geological structure, history of field development, mutual influence of wells, etc.) and can offer optimal options for distribution of injection volumes of injection wells without performing full-scale or sector hydrodynamic simulation. To predict production, we use machine learning methods (based on decision trees and neural networks) and methods for optimizing the target functions. As a result of this research, a unified algorithm for data verification and preprocessing has been developed for feature extraction tasks and the use of deep machine learning models as input data. Various machine learning algorithms were tested and it was determined that the highest prediction accuracy is achieved by building machine learning models based on Temporal Convolutional Networks (TCN) and gradient boosting. Developed and tested an algorithm for finding the optimal allocation of injection volumes, taking into account the existing infrastructure constraints. Different optimization algorithms are tested. It is determined that the choice and setting of boundary conditions is critical for optimization algorithms in this problem. An integrated approach was tested on terrigenous formations of the West Siberian field, where the developed algorithm showed effectiveness.

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

The creation and matching of an integrated field model including a model for part of a giant field, well models and surface network model is considered here. The integrated model was created using an innovative method of solving a unified system of equations that cover all the physical processes in the reservoir-well-surface network system; no integrator software was involved. The project involves a history-matched dynamic model covering part of a giant field, a surface network layout and well constructions with the subsurface equipment parameters. These data were fed to a single software product to create a digital twin which would allow simultaneous work with both the reservoir and the network. The approach enabled quick creation and matching of an integrated model with a lot of wells which can create forecasts for various operation modes and estimate the base case production for the infrastructure in place, as well as offers an option to connect new project wells to the current surface network.

The purpose of geomechanical monitoring at mineral deposits, including oil and gas, is to control the state of the rock mass, forecast possible risks and complications at all stages of the field's life: reservoir and caprock integrity failure, violation of the integrity of drilling and system of well completion, infrastructure facilities. The paper suggests approaches to the organization of a geomechanical monitoring system based on observations of displacements and deformations of the ground surface (or seafloor) during the development of reservoir and target interval. There are analytical and numerical approaches have been tested on simple models with pore pressure changes, considering the heterogeneity of elastic-strength properties.

A deep-water Field X with two major Reservoirs U and L discovered recently offshore Malaysia is on development for early production. The subsurface plan for the Field X includes water injection. But the presence of sulphate rich seawater can provide a favorable environment for souring activity to take place. This study evaluates the reservoir souring potential for the green Field X as a result of seawater flooding. Reservoir souring is the increase of the hydrogen sulfide (H2S) concentration in produced reservoir fluids. As hydrogen sulfide is a highly toxic and corrosive gas, the production of H2S has a huge impact on the safety, infrastructure and facilities of the field. Whether a reservoir is susceptible to souring is dependent on a variety of factors. Some of these include water injection flow rate, temperature of the reservoir, presence of bacterial nutrients and rock minerology. Effective prediction of biogenic reservoir souring using computer models is essential when undertaking major technical and economic decisions regarding field development. For H2S concentration calculation PETRONAS utilized in-house stand-alone modeling tool that considers physicochemical hydrodynamics of multiphase flow, heat transfer, substrate propagation and bacterial activity. The simulator looks at bacterial growth both in planktonic and sessile forms. Monod kinetics is applied for the growth of bacteria, leading to the consumption of sulphate and volatile fatty acids which in-turn is linked to H2S generation. Along with H2S propagation, H2S scavenging by rock and H2S partitioning between the various phases is also accounted for. The model can also deal with the effects of lift gas, reinjection of sour produced water, injection of biocide and nitrite. Since the Field X is a green field and historical production data is unavailable, the model is calibrated against the provided field development plan (FDP) data with sensitivity analysis. The simulation runs show that the H2S breakthrough occurs before the end of production. The amount of H2S produced indicates that the risk of reservoir souring associated with seawater injection in U and L Reservoirs of the Field X is high. It is recommended to evaluate different reservoir souring preventive measures in combination with mitigative options in terms of chance of success, risks, and cost (CAPEX/OPEX) in the context of the Field X development plan.

The existence of fluid’s compositional gradient in a reservoir drives convective flow which brings significant impacts to the operations, e.g., in formulation of injected fluid for well stimulation and enhanced oil Recovery (EOR). However, fluid compositional gradient is not always included in modeling reservoir performance due to PVT sampling limitation and simulation constraint. This work aims to show the significance of compositional convection in oil/gas reservoir and provides our experiences in dealing with this issue in Indonesian’s fields. PHE ONWJ as one of the most prolific producers of oil and gas in Indonesia currently operates an offshore block that has been producing for almost 40 years. Operating in a relatively mature well, PHE ONWJ often encounters significant fluid property change namely oil viscosity and specific gravity that changes overtime as depletion process occur. Data from X field, operated by PHE ONWJ, shows that compositional convection impacts workover and tertiary operations, by deviating from simulation results. We present the evidence of compositional convection using mechanistic models. We firstly adopt field data for setting the initial composition stratification. The stratification is identified through DST or fluid sampling. We secondly perform similarity simulation to analyze the effect of compositional gradient towards oil production. Similarity simulation is performed in the simplified domain for providing generalized solution. This solution is then scaled for the real domain. Finally, we show our approach to encounter the problems. Based on the similarity study inspired by the case of X Field, it shows that the compositional stratification affects geochemistry and near-wellbore flow behavior. The compositional convection develops multiple fluid properties at different depth, which create cross flow among layers. It also causes scale deposition in near wellbore which reduces the permeability and alters rock-fluid interactions, such as wettability and relative permeability. The alteration of near-wellbore geochemistry creates severe flow assurance issues in the wellbore. The mixing of multiple fluids from different layers cause paraffin and scale deposition. In some fields, the mixing triggers severe corrosions which could impact on wellbore integrity. The compositional stratification forces us to develop multiple treatments for different layers in single wellbore. Since the fluid’s properties are different for each layer, the compatibility between injected fluid and reservoir fluids varies.

O&G industry is facing difficult business climate with many uncertainties and challenges. Companies including National Oil Companies, NOCs have to be more efficient particularly in developing fields. The challenge is to create an environment to allow E&P companies to efficiently optimize their Field Development Plan, FDP processes and align with technology that enables integration & collaboration between different E&P domains. The environment should be agile to allow changing of circumstances while providing in-depth understanding of the risks and uncertainties involved. PETRONAS has a large portfolio of domestic and international oil & gas assets and is one of the leading NOCs in the world. With the ongoing potential of uncertainty of oil price, it is even more important to fast track field development planning while understanding the risk across domains and recognizing value from investments. PETRONAS has embarked on a digital field development pilot project called Live FDP that enriches internal existing FDP processes & tools to provide integration and generate efficiencies across multi-discipline in E&P workflows and systems that leverage on capabilities enabled by a Digital Cloud based solution. The Digital Planning Application methodology starts with Project Orchestration: Building FDPs using multi-disciplinary inputs and sensitivities followed by managing and framing via capturing an opportunity framework and concept decision. The process will then lead to generating multiple scenarios and evaluations for development options via seamless connectivity and integration with other systems in an Open Platform. At this point, process automation via connectivity of technical domain inputs to Value Based Decision Making will take place alongside Data Discovery & Benchmarks, underpinned by insights, Optimization & Advisory. The Data Analytics will then enable powerful business intelligence & analytics reporting capabilities translated into a Digital Dashboard: alignment with the UPMS process and management systems. Such systems allow project maturation to be completed fast and thus future scalability with expansion apart from Development phase to other phases such as Exploration, Drilling, Facility & Business Planning Workflows can be implemented. Based on recent internal evaluation on a pilot project in Peninsular Malaysia, by conducting Live FDP, the process efficiency in FDP evaluation scenarios was improved by up to 50% while simulation runs were shortened from 2 hrs to 20mins. On top of that, Integration & Collaboration involving benchmarking capability and via Data Ecosystem that allow cross domain collaboration between departments. This provides business continuity through data log for auditing purpose, single source of truth that leads to the increase of confidence and less uncertainties with breadth of multiple scenarios that allow techno-commercial evaluations and benchmarking with internal and external data. This paper will open up the mindset on the ways of how FDP can be developed with a new digital application that improves the project efficiency involving online cloud-based technology that allows multiple iterative processes in both technical and commercial aspects of the project. This is the new way of working that suits the difficult business climate that the O&G industry is currently facing.

The objective of the paper is to develop a mixed integer nonlinear programming (MINLP) model for optimum design and scheduling of offshore oil and gas field development in respect to simultaneous consideration of economic and environmental impact. The model is utilized as a tool for decision making management in conceptual stage. Nonlinear reservoir behavior and floating demand constraint are incorporated to improve accuracy of the solution. This paper utilizes mathematical programming techniques to address the design and scheduling problem of offshore oil and gas field development. Field development problem is first formulated into a multi-objective MINLP model incorporating many realistic features such as nonlinear reservoir behavior and floating demands. The objectives are to maximize net present value (NPV) and minimize total environmental impact (TEI) simultaneously. Environmental impact is assessed using the ReCiPe2016 method. Augmented ε-constraint method (AUGMECON) is then employed to solve the proposed multi-objective MINLP model to generate the Pareto-optimal front that is able to assist decision maker selecting the most preferred solution. The performance of the proposed modelling framework is investigated on a set of problem which consists of 2 reservoirs, 2 FPSOs, 2 customers and 5-years planning horizon. First model with single objective function to maximize NPV can be solved effectively within short computational time. The solution gives optimum decision of design, investment, production schedule, and transportation regardless the environmental impact. Then, simultaneous optimization of multi-objective MINLP with different value of ε-constraint generates multiple development schemes and objective function values. The results indicate trade-off between maximizing NPV and minimizing TEI. It is possible to obtain maximum NPV of USD 2.4 trillion at the expense of TEI which is 307.518 or to generate minimum TEI of 16.65 at the expense of NPV which is USD 74.368 billion. All possible solutions within extreme values range are presented in form of a Pareto-optimal front where TEI and NPV are plotted in x and y-axis respectively. It will assist the company to select the most preferred solution based on NPV. Consequently, the selected option brings corresponding value of TEI. Additionally, the Pareto optimal front also allows decision maker to have more flexibility to compromise between economic and environmental issues. This is the first study to consider environmental impact in the offshore oil and gas field development. Many realistic operational features such as nonlinear reservoir behavior and floating demands are also incorporated. In addition to that, the proposed framework yields a powerful tool to assist decision maker selecting the most preferred solution that satisfies their criteria in both economic and environmental aspects.

This paper presents a unique E&P knowledge management system which has been widely accepted and applied by upstream petroleum industry. This knowledge management system started in mid-1990s and consists of standard static and dynamic knowledge base, comprehensive evaluation reports, and fit-for-purpose analytics tools applicable to the entire E&P lifecycle. Emphasis is placed on illustrating the breadth and depth of the E&P knowledge and advanced analytics in terms of their capturing and applications in field development and production. This knowledge base consists of >1600 reservoirs from around the world, each containing ~400 reservoir-level static parameters and a set of dynamic performance data. The static parameter covers reservoir characteristics, fluid properties, original in-place volume, EUR, recovery factor, production-related data (such as well spacing, well pattern, well EUR et al.), reservoir management practices, and key IORs/EORs and their incremental recovery. The knowledge extraction process involves collecting, reviewing, and synthesizing geologic, reservoir engineering and production data on a representative sample of global reservoirs. The reliable, coherent, high-quality knowledge base provides a foundation for the development of primary recovery index using supervised machine learning. Insights and intelligence derived from this knowledge base are critical to decision-making for both initial or early field development and production stages. The development application includes, but not limited to: (1) quantifying in-place volume, EUR, and recovery factor; (2) characterizing possible production performance and uncertainties and obtaining a conceptual production performance curve; (3) validating development plan options; and (4) benchmarking reservoir simulation results. The production application includes: (1) benchmarking production performance; (2) identifying upside potential and improved oil recovery opportunities; (3) finding best practices and lessons learned in reservoir management and secondary recovery practice; and (4) screening EOR methods, calibrating potential incremental recovery and characterizing EOR process performance. Lack of knowledge standardization and absence of coherence of data from various data sources are the main challenges facing industry's data-driven application. The knowledge management system presented in this study provides the most reliable knowledge base, advanced analytics tools, and practical application workflow to help the upstream industry become more efficient in applying collective human intelligence.

A limited remaining reserve is one of the challenges commonly found in mature field development. Swamp fields in the Mahakam block is an example of mature field development which leads to a marginal operation. Delivering wells more economically is one of the key points to survive during those conditions. Rig operation with a significant daily expenditure could be a way for improvement to yield economic wells. In general, an efficient rig operation would deliver wells in a shorter duration and at a lower cost. In order to lessen the well duration, two aspects could be improved: performing co-activity operation to shorten the horizontal time (preparation) and mastering drilling practices to shorten the vertical time (drilling). In the co-activity operations aspect, various initiatives have been implemented, such as rigless operations, batch drilling, and offline or simultaneous activities. While in the drilling practices aspect, drilling parameters, bit design, connection practice, and team motivation were the areas that have been improved. This paper will elaborate further on those initiatives. Implementing massive co-activity operations and the best drilling practices have demonstrated a significant time saving of 24% for the shallow well (final depth around 1800 m) and 27% for the deep well (final depth around 4300 m) in the block. These practices have also made a new record of the fastest well completion in 2.17 days and the highest drilling ROP for 141 m/hour with drilling 2303 m in the first 24 hours. The record of most drilled length in 24 hours is the world best performance of RSS BHA as per Directional Driller Company worldwide record. As a result, the 2020 average cost of the shallow well was 2.6 MUSD while the deep well was 4.1 MUSD. Those massive co-activity operations and drilling practices have been properly executed since 2019 without any safety incident and related NPT. The positive results have helped the development project to survive in marginal conditions.

Target reservoir and production characterization study was carried out in Pematang Lantih field, Jambi, Indonesia. The Talang Akar Formation has 10 underlying reservoirs from 600 m to 900m TVDSS. This multi-layers sandstone structure is driven by regional tectonic stress and complicated by several faults. Sharp oil well production decline was observed during 3 years period since initial production in 2015, with GOR increase. Arresting production decline was the key objective for efficiency increase, hence improved reservoir characterization was needed, as cross-well reservoir properties/interference were unclear. Multiwell Retrospective Test (MRT) is a recent development used to study reservoirs by carrying out automatic matching of historical production rates and bottom hole. It provides practical, fast yet robust analysis for reservoir evaluation. It can quantify inter-well pressure interference and evaluate cross-well reservoir properties. The main goal of this study was to get better reservoir understanding and evaluate ability of this technique to deliver additional value at current reservoir conditions, considering initial data availability/quality. The key technology element used is multi-well pressure deconvolution, which is a highly parallelizable decoding algorithm running on multi-core workstation. The analysis is carried out on historical well pressure and production data. Hence no field operation is needed and there is no production deferment since it does not require additional field data acquisition. The technique delivers formation pressure history and productivity index history in tested well reconstruction. It is also proficient to reconstruct cross-well interference and estimate cross-well transmissibility from offset wells towards the tested well. Another result is evaluation of formation pressure decline impact on oil production of the existing wells. The study area has reservoir pressure that dropped below bubble point and continues declining. Historical data over 3 years, from a cell consisting of 4 producers was analyzed using this technique. The analysis found uniform formation transmissibility between the analyzed wells at Pematang Lantih field. Transmissibility was estimated by analyzing cross-well transient responses (CTR) calculated with multi-well deconvolution. CTR is a function representing BHP response to neighbor well single rate production. CTR is interpreted with interference test technique thus estimating transmissibility values. The analysis result confirmed that all 3 offset wells have a pressure impact towards the pressure-tested well (PLT-X) with quantified values. Connectivity analysis showed the expectation of rapid production decline if there was no pressure maintenance system. The recommendation was to estimate the economics of pressure maintenance system implementation in order to improve production performance. By using multi-well deconvolution analysis, the entire 3-years cell production history was converted into a single unit-rate pressure transient that enabled deep reservoir investigation and calculation of field reserves undisturbed by dynamic well boundaries.

Modern methods for calculating the safety factor of the sides of the open pit do not take into account the parameters of the modern geodynamic activity of the instrument array. The article presents the results of the first stage of research on the unique capabilities of radonometry to solve this problem. The studies were carried out in the instrument areas of the Shubarkol coal deposit. Terrigenous-carbonate sediments represented by fine and coarse-grained sandstones, siltstones, mudstones, loamy rocks and coals take part in the geological structure of the deposit. The stress-strain state of the rock massif in the area of the Shubarkulsky coal deposit is very heterogeneous. The nature of the deformation processes of the sides of the section is constant and moderate. Here, a discrete distribution of deformation sections is characteristic. The article presents the methods of radonometric measurements, the processing of measurement results and the results of studies of the near-surface sections of a coal mine, aimed at developing a methodology for quantitatively taking into account the degree of modern geodynamic activity in the design of open pit sides. Based on the results of radonometry, the geodynamic activity indices identified in the study of the deformation zones of the instrumentation areas are determined. An algorithm for further studies of the problem of taking into account the degree of modern geodynamic activity in determining the safety margin of open pit sides is determined.The accumulation and generalization of empirical information about the deformation processes of open pits and the results of studies of the geodynamic situation of dash sites, determined using radonometry, will make it possible to modernize the methodology for calculating the margin of safety margin of the sides.

Invalid PVT data provide high uncertainty in field development studies such as reservoir fluid compartmentalization, reserve estimation, reservoir simulation, production engineering, and surface facility design. Then, consistency check should be conducted to ensure the validity of PVT data and to identify the most representative PVT sample(s). In this paper, preliminary and complementary consistency check of PVT laboratory methods was applied to design a new comprehensive validity check procedure for verification of the reservoir fluid properties. This procedure would be ascertained whether or not the data could be used as the most representative fluid sample in further studies. The data used in this study were collected from seven undersaturated oil reservoirs, and challenges were observed through the 28 full set of available PVT laboratory data. In our study quality checking procedure of PVT samples consists of different methods such as graphical method, recombination and material balance check for well stream composition test, Buckley, modified Wilson and Hoffman plot, Watson characterization factor, Y-function of CCE test, Y-function of DL test, compositional material balance of DL test, overall mass balance for density, Bo and GOR of DL test and density check for separator test. After implementing the applicable proposed checking procedure to detect the validity of laboratory PVT sample, only 9 out of 28 PVT samples were satisfied all the preliminary and complementary check methods. Furthermore, a practical strategy, to select representative reservoir fluid sample, was also provided and discussed based on the consistency check, well condition check and comparison of fluid properties.

Reservoir characterization and modeling have become increasingly important for optimizing field development. Optimal valuation and exploitation of a field requires a realistic description of the reservoir, which, in turn, requires integrated reservoir characterization and modeling. An integrated approach for reservoir modeling bridges the traditional disciplinary divides and tears down interdisciplinary barriers, leading to better handling of uncertainties and improvement of the reservoir model for field development. This article presents the integration of seismic data using neural networks and the incorporation of a depositional model and seismic data in constructing reservoir models of petrophysical properties. Some challenging issues, including low correlation due to Simpson's paradox and under- or overfitting of neural networks, are mitigated in geostatistical analysis and modeling of reservoir properties by integrating geologic information. This article emphasizes the integration of well logs, seismic prediction, and geologic data in the 3D reservoir-modeling workflow.

It is important to fully understand faulted systems in E&P, whether for a proper understanding of prospects, optimizing well locations or enhancing field development. The identification of fractured zones within a reservoir, usually characterized by sub-seismic faults, is often neglected but can add significant value to a project. This case study focuses on the very prolific Algerian Upper Ordovician tight reservoir target. It discusses a structure at the end of an appraisal well campaign, where an integrated fracture reservoir study has been performed in order to track subtle fault corridors. The use of advanced seismic attributes from 3D multifocusing has proven invaluable when identifying fracture corridors within the reservoir. Results match reasonably well with the fracture orientation and density interpretation from cores, borehole images, and DST interpretations. This approach has proven to be of great value when planning well trajectories and predicting production. In the future, it will be used to locate development wells. Keywords: Tight reservoirs, Fractures corridors, Diffraction imaging, 3D multifocusing, Exploration, Interpretation, Algeria

The issues occur during the operation of pumping well due to the hydrodynamic imperfections. Herewith, formation permeability in bottomhole zone is broken. This value depends not only on the actual formation permeability, but on the state of well bottomhole correspondingly as well. A calculation methodology of operation of pumping well installation considering skin-zone in well bottomhole enabling to forecast the surveys on the improvement of pump efficiency is offered.

The Alma Field (formerly Argyll and then Ardmore) is located within Blocks 30/24 and 30/25 on the western margin of the Central Graben. Hamilton drilled the first discovery well 30/24-1 in 1969 and the field, named ‘Argyll’, became the first UK offshore oilfield when production commenced in 1975. Oil was produced from the Devonian Buchan Formation, Permian Rotliegend and Zechstein groups, and Jurassic Fulmar Formation from 1976 until 1992, when the field was abandoned for economic reasons. In 2002, Tuscan Energy and Acorn Oil & Gas redeveloped the field and renamed it as ‘Ardmore’. A further 5 MMbbl were produced until 2005, when the field was again abandoned due to commercial considerations. In 2011, EnQuest was awarded the licence to redevelop the field and renamed it as ‘Alma’. The field came on stream in October 2015 and has produced oil at an average c. 6000 bopd since start-up. Total ultimate recovery was expected to be about 100 MMbbl. As of end 2005, the field had produced 72.6 MMbbl as Argyll and 5 MMbbl as Ardmore. A further 4.3 MMbbl has been produced from the Alma Field to September 2017 (which includes about 0.5 MMbbl from a long-reach well drilled into the Duncan/Galia Field immediately west of Alma). In January 2020 EnQuest announced that the Alma Field would cease production early. The total production from the three phases of field development will be about 85 MMbbl of oil.

The Solan Field is a Jurassic reservoired oil accumulation located in Block 205/26a in the East Solan Basin, West of Shetland. The field was discovered in 1991 by the 205/26a-4 well which encountered oil in the Kimmeridgian to Early Volgian age Solan Sandstone and appraised between 1992 and 2009 by four wells and four sidetracks. Premier Oil farmed into Licence P.164 in 2011 and became operator. The reservoir, which is up to 100 ft thick, is a basin-floor turbidite sequence and is informally subdivided into a thick and good quality Upper Solan sandstone unit and a thinner, poorer quality, Lower Solan sandstone unit, separated by the laterally extensive Middle Solan unit. Whilst the reservoir sandstones are relatively clean (texturally and compositionally mature) and laterally extensive, sub-seismic structural and stratigraphic complexity resulted in a challenging field development. The field development to date comprises four subsea wells (two oil producers and two water injectors) tied back to a small jacket and topsides with an innovative subsea oil storage tank. Oil export is via shuttle tanker. First oil was achieved in April 2016. The field oil in place volume is in the range of 55–85 MMbbl.

The Alba Field is a relatively heavy oil accumulation lying in an Eocene deep-water channel complex in Block 16/26a of the Central North Sea. With an estimated 880 MMbbl in place, the reservoir is characterized by thick, high net/gross sands with excellent reservoir properties and rock physics favourable for seismic property detection. The field has been developed by horizontal production wells, with pressure support provided by seawater injectors. After 24 years of production, more than 427 MMbbl have been recovered. Over the course of the development, the results of development drilling and improved reservoir imaging from seismic have revealed greater reservoir complexity than anticipated at sanction. The highly irregular reservoir geometry is likely to reflect the internal stacking patterns of channel elements within the channel complex that are locally overprinted by post-depositional remobilization. This increased reservoir complexity has required more wells to effectively drain the expected volumes. Despite this, recovery has exceeded estimates from the initial field development plan, reflecting an extremely efficient waterflood. 4D seismic spectacularly images extensive sweep away from injectors and excellent reservoir connectivity. Throughout the development, the application of seismic technologies has been a key enabler for effective reservoir management and, looking forward, maximizing value.

The paper has been prepared according to a Project of Grant Financing of the Ministry of Education and Science of the Republic of Kazakhstan 2018/АРО5131591.

The Hewett Field has been in production for some 50 years. Unusually for a Southern North Sea field in the UK Sector, there has been production from several different reservoirs and almost entirely from intervals younger than the principal Leman Sandstone Formation (LSF) reservoir in the basin. Some of these reservoirs are particular to the Hewett area. This reflects the location of the field at the basin margin bound by the Dowsing Fault Zone, which has influenced structural evolution, deposition and the migration of hydrocarbons. The principal reservoirs are the Permo-Triassic Hewett Sandstone (Lower Bunter), Triassic Bunter Sandstone Formation (BSF) (Upper Bunter) and Permian Zechsteinkalk Formation. There has also been minor production from the Permian Plattendolomit Formation and the LSF. Sour gas is present in the BSF only. Several phases of field development are recognized, ultimately comprising three wellhead platforms with production from 35 wells. Gas is exported onshore to Bacton, where the sour gas was also processed. Peak production was in 1976 and c. 3.5 tcf of gas has been recovered. Hewett has also provided the hub for six satellite fields which have produced a further 0.9 tcf of gas. It is expected that the asset will cease production in 2020.

The Catcher area fields – Catcher, Varadero and Burgman – were discovered in the Central North Sea between 2010 and 2011. The three fields are found in Block 28/9a. Oil is produced from Eocene sandstones stratigraphically equivalent to the Cromarty and Tay Sandstone members of the Sele and Horda formations, respectively. The reservoir for the Catcher area fields was formed by the large-scale injection of sand from the Eocene Cromarty turbidite system into shallower Sele and Horda Formation mudstones to form the Greater Catcher area injectite complex. The Catcher area development is a floating production, storage and offloading (FPSO) based development, with 18 production and injection wells drilled from two drilling templates per field, tied back to the centrally located BW Offshore Catcher FPSO. A further development well will be drilled in 2020 to complete the base development. A phased approach to development drilling, with focused data acquisition, allowed the well layout and count to be optimized as the fields were being developed. Excellent well results have meant that the well count has been reduced relative to the development plans at sanction while delivering an increase in predicted reserves. Further infill wells and satellite field development drilling is planned for the future.

The Cygnus Field is located in Blocks 44/11a and 44/12a of the UK Southern North Sea. The field was first discovered in 1988 as a tight lower Leman Sandstone Formation gas discovery by well 44/12- 1. After the licences had sat idle for several years, GDF Britain (now Neptune E&P UK Ltd) appraised the field from 2006 to 2010. During the appraisal phase, the lower Leman Sandstone was found to be of better quality than first discovered and the gas-bearing lower Ketch Member reservoir was also encountered. The field development was sanctioned in 2012. The field has been developed from two wellhead platforms targeting Leman Sandstone and Ketch Member reservoirs. Five main fault blocks have been developed, with two wells in each fault block planned in the field development plan. The wells are long horizontal wells completed with stand-alone sand screens. At the time of writing, the production plateau is 320 MMscfgd (266 MMscfgd when third-party constraints apply), producing from nine wells with the final production well to be drilled.

The Lower Cretaceous Britannia Field development is one of the largest and most significant undertaken on the UK Continental Shelf. Production started in 1998 via 17 pre-drilled development wells and was followed by a decade of intensive drilling, whereby a further 40 wells were added. In 2000 Britannia9s plateau production of 800 MMscfgd supplied 8% of the UK9s domestic gas requirements. As the field has matured, so too has its development strategy. Initial near-field development drilling targeting optimal reservoir thickness was followed by extended reach wells into the stratigraphic pinchout region. In 2014 a further strategy shift was made, moving from infill drilling to a long-term compression project to maximize existing production. During its 20-year history the Britannia Platform has undergone numerous changes. In addition to compression, production from five satellite fields has been routed through the facility: Caledonia (2003), Callanish and Brodgar (2008), Enochdhu (2015) and Alder (2016). A new field, Finlaggan, is due to be brought through Britannia9s facilities in 2020, helping to maximize value from the asset for years to come. As Britannia marks 20 years of production it has produced c. 600 MMboe – surpassing the original ultimate recoverable estimate of c. 570 MMboe – and is still going strong today.

The article considers а mathematical model of analyzing the feasibility of an upstream project (correctional resistance model), including the formation of redundancy for correction’s implementation aimed at increasing the probability of project execution within the target efficiency metrics to the desired value of the project realization probability, as a result it allows to speak about the transition to a qualitatively new level of cooperation between stakeholders of the project, including through partnerships. This approach is applicable at all stages of oilfield development project lifecycle, for the accumulation and improvement of the project knowledge base, which is valuable for each of the project participants and significantly increases with an integrated approach to the project management.

A second seismic monitor survey acquired after nine years of production at Holstein Field was used successfully to define new wellbore sidetracks to target unswept areas in two of the main producing reservoirs (J2 and K1). The asset team and the technology group worked together to investigate the quality and interpretability of the 4D signal between the first and second monitor surveys. The method consisted of conducting a quality check of the acquisition and processing steps, modeling the amplitude variation with offset responses using existing wells to determine the response to fluid effects, and finally extracting and creating amplitude difference maps between monitor surveys for each reservoir. The interpretation of the 4D amplitude differences, combined with the analysis of production and pressure data from historical injector and producer wells, resulted in the decision to target what was interpreted to be a partially swept J2/K1 reservoir compartment by the aquifer in the southern part of the field. Well #12 was drilled in that target and encountered oil pay in both reservoirs, with low levels of water saturation. Another J2 area in the northern part of the field was interpreted to have remained partially unswept by water injectors, although seismic acoustic softening over that portion of the field suggested that it was still benefiting from injection pressure support. Well #11 was drilled in that northern portion of the field and encountered an oil-bearing reservoir with water saturation near preproduction levels and a reservoir pressure approaching original reservoir pressure, hence confirming repressurization.