Novel Approach on Thin Bed Reservoir Case Study from Muda Formation, Natuna Basin

2020 ◽  
Author(s):  
J. Panjaitan
Keyword(s):  
Oil And Gas ◽  
Reservoir Characterization ◽  
Electrical Anisotropy ◽  
High Resistivity ◽  
Petrophysical Properties ◽  
Field Development ◽  
Novel Approach ◽  
Resistivity Anisotropy ◽  
Lateral Extent ◽  
Hydrocarbon Saturation

The presence of shale in thin beds reservoirs affects formation evaluation where the standard conventional log analyses are not designed to properly correct this effect. The conventional logging tools, with low vertical resolution, are not able to characterize these thin beds. This implies that log values do not represent the true bed or layer properties, but rather an average of multiple beds. Muda Formation are characterized by thin bed layers, made up of clastic rock sequences with dominant lithology of sandstone inter-bedded with shale, siltstone, and organic material as confirmed by drilling cuttings, logs response, and also supported by observation from sidewall cores. There are many uncertainties related to the presence of thin beds, primarily sand, silt, shale or their combination in term of their petrophysical properties and lateral extent. Inadequate reservoir characterization can cause significant amounts of oil and gas to remain unidentified. Accurate petrophysical parameters determination play an important role in the development plan of a field. The lateral and vertical variations in the petrophysical properties of the reservoir lead to different scenarios of the field development. The study of Muda Formation in this structure has integrated the sidewall core and log data. The contribution of the thin sand laminae to the average log response resulted in underestimating the porosity (Ф) and hydrocarbon saturation (Sh). The advanced measurement, like the resistivity anisotropy, proved quite useful as the vertical and horizontal resistivity across these beds leading to measurable electrical anisotropy. The resistivity measured perpendicular to the bedding is significantly higher than resistivity measured parallel to the bedding. The situation occurs due to high resistivity sand layers interbedded with low resistivity shale layers. The true sand porosity and hydrocarbon saturation were calculated using the laminated sand shale sequence and calibrated with core data. The study led to the more realistic petrophysical estimation of the sand shale laminae. A combination and integration of high-resolution image log for sand count, nuclear magnetic resonance (NMR) for porosity evaluation and triaxial resistivity for volumetric model through Laminated Sand Analysis approach are found useful to solve thin bed reservoir issue.

scholarly journals A novel approach to resource potential estimation and field development of non-structural traps with limited data: a case study of Achimov formation in Western Siberia

2021 ◽  
Vol 6 (3) ◽  
pp. 52-60
Author(s):  
Daria I. Zhigulina ◽  
Dilyara I. Mingazova ◽  
Denis S. Grigoriev ◽  
Vladimir Yu. Klimov ◽  
Mariya V. Latysheva ◽  
...  
Keyword(s):  
Oil And Gas ◽  
Economic Assessment ◽  
Seismic Exploration ◽  
Resource Base ◽  
Seismic Surveys ◽  
Field Development ◽  
Estimated Parameters ◽  
Novel Approach ◽  
General Line

Background. The West Siberian basin which is one of the main oil and gas regions of Russia is characterized not only by classical structural traps but also by extremely complex geological objects of Achimov sequence. Thereby, it is quite difficult to evaluate perspectives of license areas within which we can discover those Achimov type of deposits, especially at regional stage exploration in terms of a complete absence of 3D seismic data and uneven coverage of area by 2D seismic surveys. Aim. This article is devoted to the methodology description for probabilistic assessment of the resource base of non-structural traps in the Achimov strata in areas with different 2D-seismic exploration degree. Materials and methods. The methodology based on the “density” method which in relation to the evaluated area uses statistics of estimated parameters and number of bodies in the field analogs. The general line of this paper is how to use this methodology for resource base evaluation in the zones of Achimov deposits intersection as the most promising from the point of further development. Results. As part of the project evaluation according to the proposed approach, the resource base was divided into components — resources of objects in areas of possible intersection and resources of single, non-intersecting objects. Conclusions. It provides an opportunity to spot and conduct a technical and economic assessment of previously uneconomic reservoirs.

Synergistic integration of seismic and geologic data for modeling petrophysical properties

2020 ◽  
Vol 39 (3) ◽  
pp. 164-169
Author(s):  
Yuan Zee Ma ◽  
David Phillips ◽  
Ernest Gomez
Keyword(s):  
Neural Networks ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Integrated Approach ◽  
Reservoir Modeling ◽  
Petrophysical Properties ◽  
Reservoir Properties ◽  
Field Development ◽  
Realistic Description ◽  
Geologic Data

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.

Novel Approach to Enhance Field Development Plan Process and Reservoir Management to Maximize the Recovery Factor of Gas Condensate Reservoirs Through Integrated Asset Modeling

2021 ◽  
Author(s):  
Oswaldo Espinola Gonzalez ◽  
Laura Paola Vazquez Macedo ◽  
Julio Cesar Villanueva Alonso ◽  
Julieta Alvarez Martinez
Keyword(s):  
Production System ◽  
Management Strategy ◽  
Oil And Gas ◽  
Reservoir Management ◽  
Gas Condensate ◽  
Development Plan ◽  
Recovery Factor ◽  
Integrated Analysis ◽  
Field Development ◽  
Novel Approach

Abstract The proper exploitation for a gas condensate reservoir requires an integrated collaboration and management strategy capable to provide detailed insight about future behavior of the reservoir. When a development plan is generated for a field, the reservoir management is not performed integrally, this is, different domains: geology, reservoir, drilling, production, economics, etc., work separately, and therefore, an adequate understanding of the main challenges, leading to issues such as an over dimensioning of surface facilities, excessive costs, among others. Through this paper, a methodology to improve the conventional field development plan is described, which contains 4 main pillars: Collaborative approach, Integrated analysis, engineering optimization and monitoring & surveillance. The methodology involves the description of a hybrid workflow based on the integration of multiple domains, technologies and recommendations to consider all the phenomena and compositional changes over time in the whole production system, aiming to define the optimum reservoir management strategy, facilities and operational philosophy as part of the Field Development Plan (FDP). Conventionally, the used of simplistic models most of times do not allow seeing phenomena in the adequate resolution (near wellbore and porous media effects, multiphase flow in pipelines, etc.), that occur with high interdependency in the Integrated Production System. With this methodology, the goal pursued is to support oil and gas companies to increase the recovery factor of gas condensate fields through the enhancement in the development and exploitation process and therefore, reducing associated costs and seizing available time and resources.

scholarly journals A Novel Approach to Oil Layer Recognition Model Using Whale Optimization Algorithm and Semi-Supervised SVM

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 757
Author(s):  
Yongke Pan ◽  
Kewen Xia ◽  
Li Wang ◽  
Ziping He
Keyword(s):  
Optimization Algorithm ◽  
Oil And Gas ◽  
The Other ◽  
Whale Optimization Algorithm ◽  
Classification Model ◽  
Support Vector ◽  
Recognition Model ◽  
Novel Approach ◽  
Whale Optimization ◽  
Oil And Gas Reservoir

The dataset distribution of actual logging is asymmetric, as most logging data are unlabeled. With the traditional classification model, it is hard to predict the oil and gas reservoir accurately. Therefore, a novel approach to the oil layer recognition model using the improved whale swarm algorithm (WOA) and semi-supervised support vector machine (S3VM) is proposed in this paper. At first, in order to overcome the shortcomings of the Whale Optimization Algorithm applied in the parameter-optimization of the S3VM model, such as falling into a local optimization and low convergence precision, an improved WOA was proposed according to the adaptive cloud strategy and the catfish effect. Then, the improved WOA was used to optimize the kernel parameters of S3VM for oil layer recognition. In this paper, the improved WOA is used to test 15 benchmark functions of CEC2005 compared with five other algorithms. The IWOA–S3VM model is used to classify the five kinds of UCI datasets compared with the other two algorithms. Finally, the IWOA–S3VM model is used for oil layer recognition. The result shows that (1) the improved WOA has better convergence speed and optimization ability than the other five algorithms, and (2) the IWOA–S3VM model has better recognition precision when the dataset contains a labeled and unlabeled dataset in oil layer recognition.

Center of Excellence: Leveraging Data to Reduce Incidents on Offshore Oil and Gas Assets

2021 ◽  
Author(s):  
Le Ronan Bayon ◽  
Leah Boyd
Keyword(s):  
Oil And Gas ◽  
Daily Routine ◽  
Offshore Platforms ◽  
Frontline Employees ◽  
Information Campaigns ◽  
Engineering Controls ◽  
Center Of Excellence ◽  
Novel Approach ◽  
Offshore Oil And Gas ◽  
Offshore Oil

Abstract This paper presents a novel approach to finding solutions to unsafe work practices in oil and gas environments—from manufacturing facilities to offshore platforms. The ‘Center of Excellence’ approach is a stepwise process for classifying safety events and harnessing data to reduce incidents during offshore oil and gas E&P activities. The approach includes identifying focus topics related to unsafe practices, forming cross-functional teams with significant field or impacted personnel participation, developing and implementing measures, utilizing the hierarchy of controls to mitigate the issue, and raising company-wide awareness through training and targeted information campaigns. The Center of Excellence process gives top priority to those activities in order to reduce the highest severity and most frequent safety incidents. The teams are then able to more clearly identify feasible solutions, including engineering controls, training, campaigns, and procedures to contain the hazards. The active engagement and involvement of frontline employees who either work in the field or on the factory floor is critical to understand the daily hazards of their work activities and the success of the Center of Excellence approach. With these employees acting as a champion of the developed solution, other workers are more likely to accept and adopt it in their daily routine. This paper reviews practical examples of how the Center of Excellence approach has led to safer practices in the workplace. Examples include improved safety measures for using tightening tools, which led to more than 50% reduction in hand injuries and other safety incidents. A recent example of using the approach to develop safer practices during manual handling of loads (MHL) is also presented. The examples highlight the benefits of bringing multifaceted teams and multiple industry-accepted safety concepts together to resolve common work safety challenges, which can serve as a blueprint for oil and gas companies to reduce incidents across their enterprise.

Main directions of searching for hydrocarbons in Nadym-Pursk oil and gas region

2021 ◽  
pp. 23-31
Author(s):  
Y. I. Gladysheva
Keyword(s):  
Oil And Gas ◽  
Raw Materials ◽  
Accumulation Rate ◽  
Sedimentary Basins ◽  
Seismic Exploration ◽  
Research Approach ◽  
Field Development ◽  
The North ◽  
The Sixties ◽  
Hydrocarbon Deposits

Nadym-Pursk oil and gas region has been one of the main areas for the production of hydrocarbon raw materials since the sixties of the last century. A significant part of hydrocarbon deposits is at the final stage of field development. An increase in gas and oil production is possible subject to the discovery of new fields. The search for new hydrocarbon deposits must be carried out taking into account an integrated research approach, primarily the interpretation of seismic exploration, the creation of geological models of sedimentary basins, the study of geodynamic processes and thermobaric parameters. Statistical analysis of geological parameters of oil and gas bearing complexes revealed that the most promising direction of search are active zones — blocks with the maximum sedimentary section and accumulation rate. In these zones abnormal reservoir pressures and high reservoir temperatures are recorded. The Cretaceous oil and gas megacomplex is one of the main prospecting targets. New discovery of hydrocarbon deposits are associated with both additional exploration of old fields and the search for new prospects on the shelf of the north. An important area of geological exploration is the productive layer of the Lower-Berezovskaya subformation, in which gas deposits were discovered in unconventional reservoirs.

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