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Methodical bases of differntiation of associated petroleum gas production to free gas and dissolved gas

UDK: 622.276.346.2
DOI: 10.24887/0028-2448-2019-5-86-90
Key words: associated petroleum gas, dissolved gas, free gas, hydrodynamic modeling, production accounting, regression analysis
Authors: S.D. Dariy (Rosneft Oil Company, RF, Moscow), R.R. Islamov (RN-BashNIPIneft LLC, RF, Ufa), R.R. Khaidarshin (RN-BashNIPIneft LLC, RF, Ufa), A.N. Yantudin (TNNC LLC, RF, Tyumen), A.A. Zaripov (RN-Purneftegas LLC, RF, Gubkinsky), A.Z. Kamalov (RN-Purneftegas LLC, RF, Gubkinsky), L.A. Farrahov (RN-Purneftegas LLC, RF, Gubkinsky)

The article presents the results of research conducted in terms of the differentiation of associated petroleum gas production into dissolved gas and breakthrough gas of gas caps. This task is important for the correct management of the balance of reserves and is associated with the solution of a number of methodological problems in the conditions of uncertainty of the initial data. In the work were analyzed well-known techniques and approaches to the differentiation of associated gas production, and their applicability in the conditions of the fields of RN-Purneftegas LLC was considered. Taking into account the noted advantages and disadvantages of the known approaches was chosen a technique based on the hydrodynamic modeling of the real processes of the development of the RN-Purneftegas fields. The reliability of the differentiation of produced gas for dissolved gas and gas cap gas is determined by the correct modeling the processes of liberation of dissolved gas from reservoir oil while reducing reservoir pressure and the formation of gas cones. The quality of the model setting is estimated by the technological indicators of the field development, obtained as a result of measuring flow rates, well tests, sampling and laboratory analysis of formation fluid samples. The high degree of the model matching suggests that the parameters of the reservoir during the model adaptation were chosen correctly. As a result were found the parameters related by functional dependence with the value of the model gas-oil ration by the method of regression analysis. The method based on the regression was developed for the differentiation of associated gas production wich is applicable to the fields of RN Purneftegas. The article reflects the main tasks that were solved in the course of the work, and the obtained results.

References

1. STO Gazprom RD 2.2-164-2005. Metodika planirovaniya i razdel'nogo ucheta dobychi plastovogo i tyumenskogo gazov, vypavshego v plaste kondensata i nefti pri razrabotke gazokondensatnykh mestorozhdeniy s zakachkoy sukhogo gaza v plast (Methods of planning and separate accounting of production of reservoir and Tyumen gases, condensate and oil deposited in the reservoir during the development of gas condensate fields with injection of dry gas into the reservoir), Moscow: Publ. of IRTs Gazprom, 2005, 50 p.

2. Metodika ucheta dobychi poleznykh iskopaemykh (gaz prirodnyy, gazovyy kondensat, neft' i rastvorennyy gaz) pri razrabotke mestorozhdeniy AO ARKTIKGAZ (The method of accounting for mining (natural gas, gas condensate, oil and dissolved gas) in the development of the fields of ARKTIKGAZ JSC), Materials for the round table Osobennosti razrabotki neftegazokondensatnykh mestorozhdeniy i metody ucheta dobychi poleznykh iskopaemykh (Features of the development of oil and gas fields and methods of accounting for mining), 28 p.

3. STO Gazprom 2-3.3-304-2009. Metodicheskoe rukovodstvo po razdel'nomu uchetu dobychi kondensata gazovogo i nefti pri ikh sovmestnom postuplenii v skvazhinu iz neftegazokondensatnykh zalezhey mestorozhdeniy OAO GAZPROM (Methodological guidelines for separate accounting of gas and oil condensate production when they are jointly supplied to the well from oil and gas condensate deposits of GAZPROM OJSC), Moscow: Publ. of IRTs Gazprom, 2009, 23 p.

4. Coats K.H., Thomas L.K., Pierson R.G., Compositional and Black Oil reservoir simulation, SPE 29111-MS, 1995.

5. Asalkhuzina G.F., Davletbaev A.YA., Khabibullin I.L., Modeling reservoir pressure difference between injection and production wells in low permeable reservoirs (In Russ.), Vestnik Bashkirskogo universiteta, 2016, V. 21, no. 3, rr. 537 544.

6. Bobreneva Yu.O., Davletbaev A.Ya., Makhota N.A., Estimation of reservoir pressure from the sensor data before and after injection tests in low-permeability formations (In Russ.), SPE 187763-RU, 2017.

7. Certificate of state registration of computer programs no. 2017663444, Modul' RExLab 2017 PK RN-KIM (Module RExLab 2017 for PC RN-KIM),Authors: Borshchuk O.S., Sergeychev A.V., Solov'ev D.E., Knutova S.R., Sayfullin I.F., Nuriev A.Kh., Nikonov M.A., Badretdinov T.R., Badretdinov M.R., Shtangeeva K.A., Badykov I.Kh., Makeev G.A.

8. Pedregosa F. et al., Scikit-learn: Machine learning in Python, Journal of Machine Learning Research, 2011, no. 12, pp. 28252830.

The article presents the results of research conducted in terms of the differentiation of associated petroleum gas production into dissolved gas and breakthrough gas of gas caps. This task is important for the correct management of the balance of reserves and is associated with the solution of a number of methodological problems in the conditions of uncertainty of the initial data. In the work were analyzed well-known techniques and approaches to the differentiation of associated gas production, and their applicability in the conditions of the fields of RN-Purneftegas LLC was considered. Taking into account the noted advantages and disadvantages of the known approaches was chosen a technique based on the hydrodynamic modeling of the real processes of the development of the RN-Purneftegas fields. The reliability of the differentiation of produced gas for dissolved gas and gas cap gas is determined by the correct modeling the processes of liberation of dissolved gas from reservoir oil while reducing reservoir pressure and the formation of gas cones. The quality of the model setting is estimated by the technological indicators of the field development, obtained as a result of measuring flow rates, well tests, sampling and laboratory analysis of formation fluid samples. The high degree of the model matching suggests that the parameters of the reservoir during the model adaptation were chosen correctly. As a result were found the parameters related by functional dependence with the value of the model gas-oil ration by the method of regression analysis. The method based on the regression was developed for the differentiation of associated gas production wich is applicable to the fields of RN Purneftegas. The article reflects the main tasks that were solved in the course of the work, and the obtained results.

References

1. STO Gazprom RD 2.2-164-2005. Metodika planirovaniya i razdel'nogo ucheta dobychi plastovogo i tyumenskogo gazov, vypavshego v plaste kondensata i nefti pri razrabotke gazokondensatnykh mestorozhdeniy s zakachkoy sukhogo gaza v plast (Methods of planning and separate accounting of production of reservoir and Tyumen gases, condensate and oil deposited in the reservoir during the development of gas condensate fields with injection of dry gas into the reservoir), Moscow: Publ. of IRTs Gazprom, 2005, 50 p.

2. Metodika ucheta dobychi poleznykh iskopaemykh (gaz prirodnyy, gazovyy kondensat, neft' i rastvorennyy gaz) pri razrabotke mestorozhdeniy AO ARKTIKGAZ (The method of accounting for mining (natural gas, gas condensate, oil and dissolved gas) in the development of the fields of ARKTIKGAZ JSC), Materials for the round table Osobennosti razrabotki neftegazokondensatnykh mestorozhdeniy i metody ucheta dobychi poleznykh iskopaemykh (Features of the development of oil and gas fields and methods of accounting for mining), 28 p.

3. STO Gazprom 2-3.3-304-2009. Metodicheskoe rukovodstvo po razdel'nomu uchetu dobychi kondensata gazovogo i nefti pri ikh sovmestnom postuplenii v skvazhinu iz neftegazokondensatnykh zalezhey mestorozhdeniy OAO GAZPROM (Methodological guidelines for separate accounting of gas and oil condensate production when they are jointly supplied to the well from oil and gas condensate deposits of GAZPROM OJSC), Moscow: Publ. of IRTs Gazprom, 2009, 23 p.

4. Coats K.H., Thomas L.K., Pierson R.G., Compositional and Black Oil reservoir simulation, SPE 29111-MS, 1995.

5. Asalkhuzina G.F., Davletbaev A.YA., Khabibullin I.L., Modeling reservoir pressure difference between injection and production wells in low permeable reservoirs (In Russ.), Vestnik Bashkirskogo universiteta, 2016, V. 21, no. 3, rr. 537 544.

6. Bobreneva Yu.O., Davletbaev A.Ya., Makhota N.A., Estimation of reservoir pressure from the sensor data before and after injection tests in low-permeability formations (In Russ.), SPE 187763-RU, 2017.

7. Certificate of state registration of computer programs no. 2017663444, Modul' RExLab 2017 PK RN-KIM (Module RExLab 2017 for PC RN-KIM),Authors: Borshchuk O.S., Sergeychev A.V., Solov'ev D.E., Knutova S.R., Sayfullin I.F., Nuriev A.Kh., Nikonov M.A., Badretdinov T.R., Badretdinov M.R., Shtangeeva K.A., Badykov I.Kh., Makeev G.A.

8. Pedregosa F. et al., Scikit-learn: Machine learning in Python, Journal of Machine Learning Research, 2011, no. 12, pp. 28252830.


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