Models of hydrocarbon reservoirs are highly uncertain mathematical system, because are based on a large amount of information having different levels of error. High uncertainty can lead to large amounts of additional costs for the development of a new field. Therefore, the main goal of designing development objects is to find ways to reduce these risks, including through the correct choice of a reservoir analogue. The task of searching for analogues is often associated with the search for a «twin object», i.e. the object most similar in some parameters, characteristics, etc. In the Russian Federation there is a large number of undeveloped oil and gas deposits with varying degrees of exploration, new fields and new deposits are discovered in the developed fields for which an assessment is necessary for commercial use. When developing oil and gas reservoirs, it is necessary to solve a number of problems that are not inferior in complexity to the tasks to be solved when developing deposits with hard-to-recover reserves. Given the uncertainties of a number of initial data necessary for forecasting, as well as due to the complex influence of various geological and physical factors on development indicators, the complexity and duration of correct hydrodynamic modeling of the cone formation process, often many problems are solved using the analogy method. Therefore, to predict the technical and economic indicators of the development of undeveloped oil and gas reservoirs, an important task is the reliable and reasonable choice of а reservoir analogue.

The article presents the results of scientific research in terms of the selection of an analogue object for undeveloped oil and gas reservoirs by geological and physical characteristics. This task is important for a reliable choice of analogous reservoirs and is associated with the solution of a number of methodological problems in a limited set of source data. A methodology and software module for selecting an analogous object, applicable for oil and gas reservoirs, depending on their degree of knowledge have been developed. The authors reflect the mathematical description of the algorithm; describe the main tasks that solved in the course of the work, and the results obtained.

References

1. Cosentino L., Integrated reservoir studies, Paris: TECHNIP ed., 2001, 400 p.

2. Altunin A.E., Semukhin M.V., Kuzyakov O.N., Tekhnologicheskie raschety pri upravlenii protsessami neftegazodobychi v usloviyakh neopredelennosti (Technological calculations in the management of oil and gas production in the face of uncertainty), Tyumen: Publ. of TIU, 2015, 187 p.

3. Solodov I.S., Shakshin V.P., Kolesnikov V.A. et al., Statistic approaches towards the disclosure of oil fields analogous to Samara region (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2011, no. 6, pp. 30–33.

4. Ikhsanova F.A., Ikhsanov A.I., Primenenie metoda glavnykh komponentov pri ranzhirovanii ob"ektov razrabotki (Application of the method of main components when ranking development objects), Proceedings of International conference “Sovremennye tekhnologii v neftegazovom dele – 2016” (Modern Technologies in the Oil and Gas Business – 2016), Part 2, Ufa: Publ. of USPTU, 2016, pp. 231–235.

5. Standard handbook of petroleum and natural gas engineering: edited by Lyons W., Plisga G., Lorenz M., Gulf Professional Publishing, 2015, 1822 p.

6. Rykus M.V., The influence of secondary transformations on terrigenous reservoirs quality (In Russ.), Geologiya, geofizika i razrabotka neftyanykh i gazovykh mestorozhdeniy, 2018, no. 12, pp. 40–45.

7. Shatrov S.V., Zubairov A.V., Stanekzay N.M., Integration of the geological risk into the quantitative assessment of hydrocarbon resources (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2018, no. 11, pp. 74–77.Models of hydrocarbon reservoirs are highly uncertain mathematical system, because are based on a large amount of information having different levels of error. High uncertainty can lead to large amounts of additional costs for the development of a new field. Therefore, the main goal of designing development objects is to find ways to reduce these risks, including through the correct choice of a reservoir analogue. The task of searching for analogues is often associated with the search for a «twin object», i.e. the object most similar in some parameters, characteristics, etc. In the Russian Federation there is a large number of undeveloped oil and gas deposits with varying degrees of exploration, new fields and new deposits are discovered in the developed fields for which an assessment is necessary for commercial use. When developing oil and gas reservoirs, it is necessary to solve a number of problems that are not inferior in complexity to the tasks to be solved when developing deposits with hard-to-recover reserves. Given the uncertainties of a number of initial data necessary for forecasting, as well as due to the complex influence of various geological and physical factors on development indicators, the complexity and duration of correct hydrodynamic modeling of the cone formation process, often many problems are solved using the analogy method. Therefore, to predict the technical and economic indicators of the development of undeveloped oil and gas reservoirs, an important task is the reliable and reasonable choice of а reservoir analogue.

The article presents the results of scientific research in terms of the selection of an analogue object for undeveloped oil and gas reservoirs by geological and physical characteristics. This task is important for a reliable choice of analogous reservoirs and is associated with the solution of a number of methodological problems in a limited set of source data. A methodology and software module for selecting an analogous object, applicable for oil and gas reservoirs, depending on their degree of knowledge have been developed. The authors reflect the mathematical description of the algorithm; describe the main tasks that solved in the course of the work, and the results obtained.

References

1. Cosentino L., Integrated reservoir studies, Paris: TECHNIP ed., 2001, 400 p.

2. Altunin A.E., Semukhin M.V., Kuzyakov O.N., Tekhnologicheskie raschety pri upravlenii protsessami neftegazodobychi v usloviyakh neopredelennosti (Technological calculations in the management of oil and gas production in the face of uncertainty), Tyumen: Publ. of TIU, 2015, 187 p.

3. Solodov I.S., Shakshin V.P., Kolesnikov V.A. et al., Statistic approaches towards the disclosure of oil fields analogous to Samara region (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2011, no. 6, pp. 30–33.

4. Ikhsanova F.A., Ikhsanov A.I., Primenenie metoda glavnykh komponentov pri ranzhirovanii ob"ektov razrabotki (Application of the method of main components when ranking development objects), Proceedings of International conference “Sovremennye tekhnologii v neftegazovom dele – 2016” (Modern Technologies in the Oil and Gas Business – 2016), Part 2, Ufa: Publ. of USPTU, 2016, pp. 231–235.

5. Standard handbook of petroleum and natural gas engineering: edited by Lyons W., Plisga G., Lorenz M., Gulf Professional Publishing, 2015, 1822 p.

6. Rykus M.V., The influence of secondary transformations on terrigenous reservoirs quality (In Russ.), Geologiya, geofizika i razrabotka neftyanykh i gazovykh mestorozhdeniy, 2018, no. 12, pp. 40–45.

7. Shatrov S.V., Zubairov A.V., Stanekzay N.M., Integration of the geological risk into the quantitative assessment of hydrocarbon resources (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2018, no. 11, pp. 74–77.