Computational Methodology to Study Heterogeneities in Petroleum Reservoirs
- J. T. Cevolani (Federal University of Espirito Santo) | A. E. Mostafa (University of Calgary) | E. A. Vital Brazil (University of Calgary) | L. Costa de Oliveira (Federal University of Espirito Santo) | L. Goliatt da Fonseca (Federal University of Juiz de Fora) | M. Costa Sousa (University of Calgary)
- Document ID
- Society of Petroleum Engineers
- EAGE Annual Conference & Exhibition incorporating SPE Europec, 10-13 June, London, UK
- Publication Date
- Document Type
- Conference Paper
- Society of Petroleum Engineers
- 1.2.3 Rock properties, 7.6.6 Artificial Intelligence, 4.1.5 Processing Equipment, 1.6.9 Coring, Fishing, 5.1.8 Seismic Modelling, 5.6.1 Open hole/cased hole log analysis, 5.7.2 Recovery Factors, 5.1.2 Faults and Fracture Characterisation, 2.4.3 Sand/Solids Control, 5.5.2 Core Analysis, 1.14 Casing and Cementing, 5.1 Reservoir Characterisation, 5.1.1 Exploration, Development, Structural Geology, 4.3.4 Scale, 4.1.2 Separation and Treating, 5.5.4 Visualization Technologies
- Optimization, Computational Tool, Reservoir Characterization, Petrofacies, Diagenesis
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Characterization of hydrocarbon reservoirs is strategically important to define the productivity of oil and/or gas fields. It involves many challenges such as appropriate identification, classification and interpretation of diagenetic processes that directly affect the quality of the reservoirs. Proper studies demand integration and analysis of very large amounts of data, usually presenting high-dimensional feature spaces. Current methods have many manual steps leading to a limited exploration of the data. These challenges are being intensified due to the need of knowledge and time dedication from experts. We developed a novel methodology that combines established techniques, such as Principle Component Analysis (PCA), clustering methods, parallel coordinates and scatter plots, with features such as dynamic (magic) lenses - filter and shadow lenses -, axes reordering and color maps, to automatically perform reservoir characterization in order to assist the identification, validation and interpretation of petrofacies. Petrofacies is a set of petrographic characteristics of microscopic order which allow the analyst to understand the diagenetic processes, aiding in the evaluation of the potential for hydrocarbon storage in the reservoir. We have applied our methodology on several databases from different sedimentary basins - Espirito Santo and Parana basins (Brazil), Talara Basin (Peru) and Niger Delta Basin (Nigeria). We conclude that our method allows the analyst to gain insights about the entire database in a manner that is faster than the analysis using a manual method. It also allows validation of the results because it is a powerful tool that can qualitatively and quantitatively support the analyst in the identification, interpretation and validation of petrofacies. This new methodology can optimize data analysis of similar databases, accelerating the analysis and reducing the committed work by the experts.
Prediction models, the mapping of distribution of heterogeneities, and reservoir quality are very important for performing tasks such as exploration and production optimization of hydrocarbon fields. Normally all steps for the geological sampling process, data generation and their interpretation are carried out by manual methods. These are time consuming methods and take a long time to complete due to the very large amount of data that the geologist has; the large volume of information is cumbersome to use.
Heterogeneities control the amount of hydrocarbon that may be in a reservoir and the recovery efficiency. Therefore, for a good characterization, it is necessary to describe the lithologic structure and the distribution of diagenetic changes in the reservoir (Mukerji, T. et al, 2001). This analysis can be done in a multi-scalar way, which is now one of the primary methods used to evaluate the quality of reservoirs (Küchel and Holz, 2002). It includes 5 heterogeneity levels: from heterogeneities in depositional sequences (level 1) to heterogeneities of the grain, cement and pores (level 5), which have a higher resolution degree. The analysis for this last level is carried through sedimentary petrography techniques that have the ability to meaningfully characterize voids that are capable of storing oil, gas and/or water. In this work we use an analysis based on Level 5: grain, cement and pores.
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