Development Of Hydrocarbon Fields Research Articles

Морская транспортировка нефти на экспорт с месторождений Арктики

The prospects for the development of transportation of crude oil from the Arctic shelf, incl. in the Eastern sector of the Russian Arctic are analyzed. Projects for the production and resources of hydrocarbons have been identified and mentioned ones will become the basis for the development of cargo transportation along the NSR in the medium and long term. The study of existing options for the transportation of hydrocarbons from the shelf of the Far East and the Russian Arctic showed the relevance of using schemes using shuttles and floating oil storage facilities. The expert approach identified the key groups of vessels necessary for the implementation of work on the shelf. The structure of fleet demand visualized in the article takes into account technologies for the development and maintenance of offshore hydrocarbon fields. As an example, the calculation of the required number of shuttles with transshipment through a floating oil storage facility or directly to the port of destination from an offshore ice-resistant fixed platform in key directions was made. The tanker Vasily Dinkov (Panamax type) and the tanker Gulf America (Aframax type) were used as prototypes. The key aspects that need to be taken into account when using the specified technological scheme of transportation are highlighted: ensuring year-round transportation; taking into account best practices and compatibility with existing schemes for the delivery of crude oil to the final ports of destination; optimal choice of transshipment points. It is also necessary to clarify the size groups of vessels on each of the routes and the size and type of floating oil storage facilities. Since the Arctic is a very sensitive area to the impact of the man-made environment, special attention is paid to environmental risks that increase with the intensification of navigation in the NSR water area.

Lateral Rock Characteristic Evidence of Hydrocarbon Restoration from Post-Stack Impedance Inversion: A Case Study of ZED-field Offshore Niger Delta

Lateral predictions of rock properties that are descriptive of a reservoir have been studied using a model-established seismic inversion approach that was used to convert input seismic data into an acoustic impedance structure to optimize hydrocarbon restoration in the field. This was actualized by integrating wireline logs and 3D post stack seismic data procured from ZED-Field offshore Niger Delta. The inversion system employed in this study comprises of forward modelling of reflection coefficients starting with a low-frequency impedance model induced from well logs and convolution of the reflection coefficients with the source wavelet extracted from the seismic input. P-impedance analysis at reservoir C5000 delineated from the control well gave a near perfect correlation of 0.998109 (≈ 99.8 %) between the original P-impedance log, initial P-impedance model log and inverted P-impedance log with an estimated error of 0.0616932 which is about (6.16%). Seismic inversion analysis realized an acoustic impedance structure with P-impedance values ranging from 3801 to 11073.0m/s*g/cc and having an overall increase with depth tendency. Specifically, a low-impedance structure was observed at the reservoir window that can be profiled laterally elsewhere from the existing wells. Impedance slices extracted from the impedance volume at the top and base of reservoir C5000 clearly showed low impedance values away from the existing wells which are evidence of new hydrocarbon prospects (hydrocarbon-charged sands) in the field that can be explored for improved hydrocarbon recovery and field development. Therefore, the realized attribute could supply litho-fluids knowledge inside the current reservoirs, and likewise aid in defining probable hydrocarbon regions of low impedance that can be tested with the input seismic to boost the interpretation of reservoir attributes with feasible integration to seismic stratigraphy for improved reservoir prediction away from the extant wells. This information can be invaluable in delineating more prospective reservoir zones in the field, and thereby enhancing optimum field development which aids in reservoir management decisions.

Justification of the boundary values of open porosity and gas permeability using data from flow studies for porous carbonate reservoirs

This paper proposes a method for determining the boundary values of open porosity (KPO_GR) and gas permeability (KPR_GR) of porous-type carbonate reservoir rocks using the example of Tournaisian deposits of one of the oil fields of the Republic of Tatarstan. When justifying the boundary values, two databases on core studies are used: 1) on standard core studies (used mainly to calculate hydrocarbon (HC) reserves); 2) on special core studies (used for technological development projects). In the proposed method, the residual oil saturation factor is not a constant, but is taken from flow studies or calculated from core dependencies. When determining the lower limits of porosity and permeability from both databases, approximately the same boundary values were obtained: KPO_GR = 0.11 fr. un., KPR_GR = 2·10–3 μm2 and KPR_GR = 1.7·10–3 μm2, but they differ from the values, accepted by petrophysicists when calculating the reserves of considered deposit – KPO_GR = 0.09 fr. un., KPR_GR = 1·10–3 μm2. Such a difference in determining the boundary porosity can significantly affect the calculation of hydrocarbon reserves, technological calculations and field development planning.

Вопросы стратегического управления в нефтегазовых компаниях при освоении арктических месторождений

The current development of hydrocarbon fields in the Arctic necessitates innovation-driven solutions regarding technology and management. While extensive production experience exists in onshore projects, the complexities of offshore hydrocarbon fields, such as limited access and underdeveloped infrastructure, demand strategic decisions in an unstable market environment. Long-term in nature, these decisions require a comprehensive application of strategic management methods and tools. The irreversibility of economic processes associated with substantial investments and the potential for major financial losses in project failure underscore the importance of employing strategic management methodologies. Global factors such as fluctuating oil prices, geopolitical challenges, the rise of green energy, and heightened corporate social responsibility expectations in the oil and gas sector necessitate a reevaluation of fundamental principles in strategic management systems. This study employs logical and general research methods to classify and synthesize relevant literature, identifying strategic management issues and evolving principles and approaches in strategy formulation. Technical and economic aspects of project implementation onshore and offshore are highlighted. The article argues for the revision of strategic management principles in Arctic oil and gas projects, particularly in offshore field development. Conceptual models of functional strategies for business units implementing onshore and offshore projects are proposed.

Plugging of wells taking into account man-made deformation processes during hydrocarbon field development

The development of the technology of viscous-plastic plugging of wells, taking into account the negative consequences of man-made deformation processes, is shown. The analysis of patent information on new technologies aimed at improving the insulating properties of plugging compounds is carried out.

Application of two classes of inverse problems for optimization and management of the natural hydrocarbon field development process

The article considers two classes of inverse problems in the modeling of hydrocarbon field development: optimization and adaptation of the development history. They jointly form the basis for field development management in a closed loop, based on a constantly updated 3D geological and technological model. The problems of model adaptation (identification) arise due to the point-by-point measurements and the inaccuracy of determining the initial data on porosity and permeability of the host rocks and other parameters of the deposit when building the 3D model. Such problems are regarded as the inverse ones, because the consequence – field measurements – is used to determine their cause. The problems under consideration are related to the identification of both porosity and permeability of the reservoir and other key parameters that determine the dynamics of development. Geologically consistent formulation ensures that the adapted model retains the original geological principles of the distribution of reservoir properties. The second class of problems under consideration is the problems of optimization (regulation) of development. One of the sought-after formulations is related to the optimal redistribution of a given target level of production from the field to all production wells in time. In this case, the technological limitations of surface equipment are taken into account. The maximized criterion reflects the economic effect of the asset development. In this article, without going into details of mathematical realization, the authors consider practical examples of solving these problems using full-scale 3D multiphase filtration models of the real fields. The algorithms based on the current methods of optimal control theory are used, which were developed and implemented by the researchers of Oil and Gas Research Institute of the Russian Academy of Sciences in the SimMatch software package and confirmed their effectiveness on numerous synthetic and real examples. Application and further development of these methods within the framework of a single loop, taking into account continuous information from the entire set of sensors, will significantly increase the efficiency of intelligent wells and field control systems.

GENERALIZATION OF PROSPECTIVE TECHNOLOGIES FOR INCREASING HYDROCARBON EXTRACTION FROM NATURAL GAS FIELDS

The vast majority of hydrocarbon fields in Ukraine are at the final stage of development, characterized by complicated conditions for hydrocarbon production. The difficulty of extracting residual hydrocarbon reserves is associated with low reservoir pressures, high water cut, destruction of the bottomhole formation zone, and corrosion of underground and surface equipment. The depletion of the main fields in terms of production and reserves leads to a decrease in hydrocarbon production levels. The fields discovered in recent years are characterized by a complex structure, large depths of productive reservoirs, insignificant reserves and cannot significantly affect the maintenance of hydrocarbon production. Therefore, the main potential reserve for increasing production levels is the residual reserves of depleted fields. The raw material base of such reservoirsis characterized by a deterioration in the quality and structure of reserves over time and is accompanied by an increase in the share of hard-to-extract reserves. To increase the efficiency of development of proven hydrocarbon reserves, existing approaches have been improved and new approaches have been developed for the extraction of hydrocarbons from watered formations, the extraction of retrograde condensate that fell during the development of gas condensate fields for depletion, and the cleaning of bottomhole zones of gas and gas condensate wells and wells. Negative influence of complicating factors during their operation. However, increasing the efficiency of oil and gas field development is possible by investing in the implementation of developed technologies, which will increase their production capabilities in conditions of a significant shortage of hydrocarbon raw materials in Ukraine. Due to the high technological efficiency of secondary technologies for the development of hydrocarbon fields, which is also confirmed by industrial data, their implementation in the fields of Ukraine is recommended.

Three-Phase Dynamical Systems and Their Applications to Monitoring for the Development of Hydrocarbon Fields

Three-Phase Dynamical Systems and Their Applications to Monitoring for the Development of Hydrocarbon Fields

Geomechanical Response in Energy Transition Applications: Assessing its Role with Data Assimilation

The subsurface is characterized by significant uncertainties that pose challenges for geothermal energy production, CO2 sequestration, and hydrocarbon field development. To handle this uncertainty, engineers often use ensembles of models with different porosity and permeability distributions. In addition, history-matching procedures can further reduce uncertainty. However, traditional methods using well bottom hole pressures as observations can be challenging for geothermal or CO2 sequestration projects with a limited number of wells. To overcome this limitation, additional observation data can be used. In this study, we propose using vertical displacements to evaluate the subsidence/uplift of the model. Pressure depletion, for example, leads to surface subsidence due to rock compaction. We suggest measuring subsidence during field development and using it as an objective function to minimize the difference from measured data. Our approach provides a more reliable and accurate way to evaluate the model's subsurface behavior, helping to reduce uncertainties in geothermal energy production, CO2 sequestration, or hydrocarbon field development.
 We used a state-of-the-art simulator called DARTS [1] to simulate fluid flow in the subsurface, and computed geomechanics response using a physics-based proxy. We then performed history matching using ensemble smoother with multiple data assimilation (ES-MDA) of the reservoir subsidence to better understand the reservoir properties, such as permeability [2]. Our workflow involved generating an ensemble of models with varying permeability and computing vertical displacements using the physics-based proxy model for geomechanics [3]. We then applied ES-MDA to find the model with permeability that fits best to the reference subsidence surface. Flow pattern in heterogeneous reservoir determines in-situ stress changes, which could induce seismicity in a presence of natural faults. We used fault slippage criteria for each scenario. Data assimilation procedure provide us history matched model, and, therefore, more reliable assessment of induced seismicity risk. We used 2.5D extruded mesh with heterogeneous permeability and uniform geomechanical properties.

Prediction of water breakthrough during waterflooding under unstable water displacement front conditions

Unsteady modifications of waterflooding technologies are usually used as the main technique of reservoir pressure maintenance and enhanced oil recovery in the development of hydrocarbon fields. The disadvantages and imperfections of the conventional approach remain even after wide application of geological and hydrodynamic mathematical modeling and its truncated modifications, including proxy models, synthetic models and other simplified versions. At this stage it was not possible to achieve a fullfledged unification of waterflooding technology, because the theory of two-phase flow filtration created by Buckley-Leverett does not allow taking into account the influence of instability of the displacement front and its negative consequences, provoking a jump change and triple water saturation. This study attempts to return to the solution of this problem and proposes an alternative concept of monitoring and optimization of unsteady waterflooding of oil deposits, taking into account the consequences of instability of the front of oil displacement with water. Keywords: water flooding; water saturation; instability of the displacement front; optimization; catastrophe theory; phase plane.

A machine learning approach for the prediction of pore pressure using well log data of Hikurangi Tuaheni Zone of IODP Expedition 372, New Zealand

Pore pressure (PP) information plays an important role in analysing the geomechanical properties of the reservoir and hydrocarbon field development. PP prediction is an essential requirement to ensure safe drilling operations and it is a fundamental input for well design, and mud weight estimation for wellbore stability. However, the pore pressure trend prediction in complex geological provinces is challenging particularly at oceanic slope setting, where sedimentation rate is relatively high and PP can be driven by various complex geo-processes. To overcome these difficulties, an advanced machine learning (ML) tool is implemented in combination with empirical methods. The empirical method for PP prediction is comprised of data pre-processing and model establishment stage. Eaton's method and Porosity method have been used for PP calculation of the well U1517A located at Tuaheni Landslide Complex of Hikurangi Subduction zone of IODP expedition 372. Gamma-ray, sonic travel time, bulk density and sonic derived porosity are extracted from well log data for the theoretical framework construction. The normal compaction trend (NCT) curve analysis is used to check the optimum fitting of the low permeable zone data. The statistical analysis is done using the histogram analysis and Pearson correlation coefficient matrix with PP data series to identify potential input combinations for ML-based predictive model development. The dataset is prepared and divided into two parts: Training and Testing. The PP data and well log of borehole U1517A is pre-processed to scale in between [-1, +1] to fit into the input range of the non-linear activation/transfer function of the decision tree regression model. The Decision Tree Regression (DTR) algorithm is built and compared to the model performance to predict the PP and identify the overpressure zone in Hikurangi Tuaheni Zone of IODP Expedition 372.

Azimuthal Prestack Seismic Anisotropic Inversion on a Deep and Tight Carbonate Reservoir From the North Potwar Basin of Pakistan

Summary Quantitative characterization of deep, tight, and heterogeneous reservoirs plays an important role in identifying hydrocarbon pathways for effective and optimal reservoir field development. In this case study, we used an azimuthal prestack seismic anisotropic inversion approach to estimate attributes of horizontal transverse isotropy (HTI) caused by a set of vertical fractures, oriented cracks, and stress. Anisotropic inversion facilitated the conversion of interface properties to the corresponding layer-based properties, which led to the quantitative interpretation of reservoir properties related to azimuthal variation in seismic amplitudes. To estimate the anisotropy magnitude and the direction of the isotropy axis in HTI media, elastic properties (P-impedance and Vp/Vs) obtained from prestack seismic inversion (using six azimuth × four angle stack) served as inputs. The isotropic low-frequency model (LFM) is used as the foundation of the inversion for all azimuths, and the anisotropy effects are later added by updating the model along the azimuths. The direction of the isotropy plane resulting from the anisotropic inversion is determined by using the maximum horizontal stress as a prior constraint, which eliminates any inherent uncertainty. The workflow used effectively characterized the orientation and density of fractures from the recently discovered oilfield reservoirs of the Paleocene (Lockhart) formation located in Pakistan’s north Potwar Basin. It also helped improve the prediction accuracy for fractures in the study area. According to the observations (fractures) from the exploratory drilled well (D1) in the tight carbonate (Lockhart) reservoir, a significant amount of anisotropy magnitude is observed. This provides the basis for hydrocarbon exploration, field development, and reliable drilling decisions.

Modeling Permeability Using Advanced White-Box Machine Learning Technique: Application to a Heterogeneous Carbonate Reservoir.

From exploration to production, the permeability of reservoir rocks is essential for various stages of all types of hydrocarbon field development. In the absence of costly reservoir rock samples, having a reliable correlation to predict rock permeability in the zone(s) of interest is crucial. To predict permeability conventionally, petrophysical rock typing is done. This method divides the reservoir into zones of similar petrophysical properties, and the permeability correlation for each zone is independently developed. The challenge of this approach is that the success depends upon the reservoir's complexity and heterogeneity and the methods and parameters used for rock typing. As a result, in the case of heterogeneous reservoirs, conventional rock typing methods and indices fail to predict the permeability accurately. The target area is a heterogeneous carbonate reservoir in southwestern Iran with a permeability range of 0.1-127.0 md. In this work, two approaches were used. First, based on permeability, porosity, the radius of pore throats at mercury saturation of 35% (r35), and connate water saturation (Swc) as inputs of K-nearest neighbors, the reservoir was classified into two petrophysical zones, and then, permeability for each zone was estimated. Due to the heterogeneous nature of the formation, the predicted permeability results needed to be more accurate. In the second part, we applied novel machine learning algorithms, modified group modeling data handling (GMDH), and genetic programming (GP) to develop one universal permeability equation for the whole reservoir of interest as a function of porosity, the radius of pore throats at mercury saturation of 35% (r35), and connate water saturation (Swc). The novelty of the current approach is that despite being universal, the models developed using GP and GMDH performed substantially better than zone-specific permeability, index-based empirical, or data-driven models used in the literature, such as FZI and Winland. The predicted permeability using GMDH and GP resulted in accurate prediction with R2 of 0.99 and 0.95, respectively, in the heterogeneous reservoir of interest. Moreover, as this study aimed to develop an explainable model, different parameter importance analyses were also applied to the developed permeability models, and r35 was found to be the most impactful feature.

Application of a Modular Dynamic Formation Tester on a Wire Line to Refine the Filtration Characteristics of the Production Formations of the Magovsky Oil and Gas Condensate Field

An important task in monitoring the development of hydrocarbon fields is to obtain data on the filtration characteristics of reservoirs and the properties of fluids in reservoir conditions. When using standard logging in the complicated conditions of low-permeability formations, poorly consolidated rocks and eroded wellbores, it is very difficult to perform reservoir pressure measurements, sampling with a detailed analysis of fluid properties. A study was carried out in order to clarify the filtration properties of the rocks of the geological section by the method of hydrodynamic logging with testing of the formations by a tester on a MDT logging cable (modular dynamic tester). This problem was solved using the example of carbonate production formations of the Magovskoye oil and gas condensate field, which are generally characterized by a complex heterogeneous structure. An analysis of the effectiveness of using a modular dynamic reservoir tester made it possible to clarify the boundaries of permeable rock intervals with an assessment of their saturation. At the same time, working intervals of the geological section were established, which, with standard logging, were interpreted as dense rocks.

Chapter 9. Application of sequence stratigraphy to the evaluation of selected North Sea Jurassic hydrocarbon fields and carbon capture, utilization and storage (CCUS) projects

Abstract The application of sequence stratigraphic concepts and methods augments the efficient development of North Sea hydrocarbon fields with Jurassic reservoirs. In particular, the approach provides enhancements to the development of robust reservoir zonations, more accurate assessments of the extent and continuity of reservoir zones and flow units, clearer identification and prediction of the most productive reservoir intervals, improved understanding of field-wide pressure barriers or baffles to fluid flow, and enhanced reservoir models. In addition, carbon capture and storage (CCS) projects in Jurassic rocks will benefit from the adoption of a sequence stratigraphic approach by enhancing the understanding of storage unit architecture, connectivity and top seals. In this chapter, these applications are discussed with reference to around 20 case studies from the North Sea Basin.

Petrophysical properties of igneous rocks in continental rift basins – a case study from the Mesozoic sequence of the Browse Basin, North West Shelf of Australia

Capturing the ubiquitous distribution and properties of igneous rocks is necessary to succeed in hydrocarbon exploration, field development and underground gas storage when dealing with magma-rich rift margins. In recent years, numerous researches have revealed detailed morphologies of intrusive and extrusive rock units embedded within sedimentary basins owing to advances in 3D seismic data. Outcrop studies have also provided deeper understandings of their occurrence and geometries. However, there has been comparatively little focus on the rock physics of igneous bodies and their relationships to seismic expression. To bridge this gap between the outcrop and the seismic information, we undertook a well-log-based petrophysical study of igneous rocks using subsurface dataset from the Browse Basin located in the Australian North West Shelf. In this contribution, we describe a classification of volcanic facies (e.g. lava flows, volcaniclastics, intrusive sills) based on well log motifs and textures apparent in borehole image data. Statistics of the petrophysical properties of each volcanic facies are also analysed in order to examine their correlation to seismic patterns. Our study implies the importance of detailed characterisation of igneous petrophysical properties of igneous rock units where concentrated within a sedimentary basin, which will help reconcile interpretations of seismic data.

Numerical solution of the control problem on the depletion of gas reservoirs with weakly permeable top

The current stage in the development of mathematical and software support for the processes of designing the development of hydrocarbon fields is characterized not only by the improvement of the means of geological and hydrodynamic modeling of reservoir fluid filtration but also by the use of algorithms for optimizing the development of gas deposits. The paper considers the problem of optimal control of the depletion of a gas reservoir with a low-permeability top. Using the so-called Myatiev-Girinsky hydraulic scheme, a two-dimensional equation describing the unsteady gas flow in a reservoir with a jumper is averaged over the capacity of the productive reservoir. This comes down to a one-dimensional equation with an additional term, taking into account gas-dynamic relationships between the reservoir and the jumper. For the numerical solution of process control problems, a formula for the gradient of the functional characterizing the reservoir depletion is found, and the method of successive approximations based on Pontryagin’s maximum principle is applied. In this case, the direct and conjugate boundary value problems are solved by the method of straight lines, and the required flow rate, without taking it beyond the maximum and minimum possible, is found by the gradient projection method with a special choice of step. A brief block diagram of the algorithm for solving the problem is shown; on its basis, a computer program was compiled. The results of calculations are presented to identify the influence of the values of the complex communication parameter not only on the state of the object but also on the operating mode of the well. The expediency of using the presented optimization tool is dictated by an increase in the share of deposits

Integrating facies analysis and geostatistical methods in an onshore oil field using petrophysical groups

Reservoir facies studies are of great importance in different stages of exploration and development of hydrocarbon fields. We have aimed to generate a reservoir facies model for the Asmari Formation in an onshore oil field located in southwest Iran. Input data for electrofacies (EF) clustering algorithms are used, which include gamma-ray (GR), density (RHOB), porosity, and sonic logs from four wells. We obtain the petrophysical group (PG) and EF class using core drill data (mercury injection capillary pressure) and well-logs analysis. The integration of PGs and log EF significantly decreases the uncertainty in reservoir modeling, which alternatively enhances field development decisions. We compare the multiresolution graph-based clustering (MRGC) and k-means clustering methods. EF clustering results find nine EF classes. We delineate high-quality reservoirs based on lower GR, RHOB, and high-porosity logs. Next, we use the clustering results in the static reservoir modeling process, using the sequential index simulation and indicator kriging methods. The comparison between the facies obtained models and existing drilling core data finds that the absolute percentage error of the MRGC algorithm is less than that of the k-means algorithm. The results obtained by this study can provide useful information for the development of hydrocarbon exploration plans in the studied oil field.

Geological and hydrodynamic modeling as a tool for improving the methodology of designing the development of hydrocarbon deposits at the final stage

The main task of design and development of hydrocarbon fields is the most complete extraction of their geological reserves with maximum economic efficiency. To solve this problem, the present work improves the methodology of development design in the direction of maintaining a stable operating fund, by sidetracking in idle and low-yield wells of fields at the late stage of development, the basis is geological and hydrodynamic modeling of reservoir parameters and filtration processes of reservoir fluids. The adaptation of the development history and its subsequent prediction allows optimal and cost-effective designing of the hydrocarbon field development using high-technology workover (HWR) of idle and marginal wells in order to restore their operation with higher productivity.

Local mean imputation for handling missing value to provide more accurate facies classification

The search for oil and gas reserves is an ongoing challenge. The possibility of oil and natural gas reserves running out in Indonesia in less than 25 years must also be considered by the industry. Unfortunately, the process of exploration and development of hydrocarbon fields still has its challenges, one of which is knowing the characteristics of hydrocarbon reservoirs. One of these characteristics that should be analyzed is rock facies. This could be done by using core data, well logs, analog studies, and others. However, this method is very expensive and time-consuming. Currently, the machine learning approach is the most popular solution for the classification of rock facies. However, a common issue with this method is the missing values due to recording errors in the field. Meanwhile, a machine learning system requires accurate data to form a good model. Therefore, we propose the use of a simple imputation method to solve the local mean imputation method by considering the uniqueness of each class before performing the imputation process. We also implemented several popular boosting methods in machine learning such as comparing Extreme Gradient Boosting and Light Gradient Boosting with several machine learning algorithms that are often used in solving facies classification problems such as Random Forest, Decision Tree, Support Vector Machine, and K-Nearest Neighbor. According to our results, the Local Mean imputation method improved the model's performance, where the perceived increase was between 1-10% and the model with the best performance was generated by the Random Forest method.