Quantitative assessment of areal geological complexity

Background. The article presents a new approach to assessing the geological complexity — quantitative assessment of areal complexity, as well as an alternative methodology for assessing complexity in 1D.

Aim. Developing a numerical metric for assessing the geological complexity and creating an algorithm for complexity maps construction.

Materials and methods. Generally, complexity describe the reservoir in one number, that often underestimates the real complexity of the deposit. Geological complexity, presented in the article consists of 5 groups: structuraltectonic, facies-lithological, permeability and porosity, secondary alteration and fluid properties, 13 characteristics describe the complexity space of these groups. Each of these characteristics could be presented not only in 1D but also in 2D. The proposed methodology was tested on the company’s assets.

Results. The presented examples of complexity maps for several fields show the advantage of 2D complexity estimation in comparison with 1D. The analysis of decomposed complexity estimation (for individual groups) on the company’s assets showed that the key groups of complexity are structural-tectonic, facies-lithological characteristics. Therefore, characteristics that describe these groups should be taken into account during the decision-making process and assets ranking.

Conclusion. A methodology of quantitative assessment of areal geological complexity has been developed. This areal assessment allows identify the most “problematic” areas, analyzing existing sources of uncertainty, and also ranking and screening company assets when making strategic decisions.

geological complexity, geological structure, characteristics of geological complexity, complexity metric, complexity code, complexity map

1. Головченко М.А., Кудашов К.В., Филимонов В.П., Рахимов Т.Р. Методика определения индекса сложности и геонавигации скважин (GDI) и их классификация // 3-я научно-практическая конференция «Горизонтальные скважины 2019». EAGE. — 2019. — 4 с.

2. Hidalo C.A., Hausmann R. The building blocks of economic complexity // PNAS. — Vol. 106. — 2009. — 6 p.

3. Jia L., John A., Kumar N., Bialas R., Lanson T.P., Jing X.D. Novel benchmark and analogue method to evaluate heavy oil projects // SPE-184101-MS. — 2016. — 12 p.

4. Kovalevskiy E. Geological modeling on the base of geostatistics. Course Note // Student lecture Tour, RUSSIA& CIS. — 2011–2012. — 122 p.

5. Lobo J., Helbing D., Kühnert Ch., West G.B. Growth, innovation, scaling, and the pace of life in cities // PNAS. — Vol. 104. — 2007. — 33 p.

6. McDonough J.M. Lectures on computational numerical analysis of partial differential equations. Chapter 2: Numerical Solution of Elliptic Equations // Departments of Mechanical Engineering and Mathematics. University of Kentucky. — 2008. — 169 p.

7. Наугольнов М.В., Большаков М.С., Мейнарендс Р. Новый подход по оценке индекса сложности разработки месторождений Западной Сибири // SPE — 187780-RU. — 2017. — 17 с.

8. Nishikori N., Sugai K., Normann C., Onstein A., Melberg O. An integrated workflow for gas injection EOR and a successful application to a heterogeneous sandstone reservoir in the southern North Sea // IPTC 12025. — 2008. — 14 p.

9. Nzeda B.G., Schamp J.H., Schmitt Th. Development of well complexity index to Improve risk and cost assessments of oil and gas wells // IADC/SPE 167932. — 2014. — 14 p.

10. Ranjan R., Rizal M., Soni S., Masoudi R. Reservoir benchmarking to unlock further development of Malaysian oil fields // SPE-196443-MS. — 2019. — 11 p.

11. Samson M., Deutsch C. Collocated Cokriging // Retrieved from: https://geostatisticslessons.com/lessons/ collocatedcokriging. — 2020. — 11 p.

12. Wellmann J.F., Regenauer-Lieb K. Uncertainties have a meaning: Information entropy as a quality measure for 3D geological models // Tectonophysics. — Vol. 526–529. — 2012. — 10 p.

13. West G.B., Brown J.H., Enquist B.J. A general model for the origin of allometric scaling laws in biology // Science. — Vol. 276. — 1997. — 6 p.

14. Wickens L.M., Kelly R. Rapid Assessment of Potential Recovery Factor: A New Correlation Demonstrated on UK and USA Fields // SPE 134450. — 2010. — 6 p.