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Creation of software tool for long-term investment planning with a view to the effective development of oil fields

UDK: 622.276.6
DOI: 10.24887/0028-2448-2019-12-128-131
Key words: recoverable reserves, residual reserves, production wells drilling, geological and technological activities, hydraulic fracturing, well workover, optimal planning of geological and technical activities, machine learning, neural network
Authors: A.V. Nasybullin (Almetyevsk State Oil Institute, RF, Almetyevsk), Ram.Z. Sattarov (TatNIPIneft, RF, Bugulma), F.M. Latifullin (TatNIPIneft, RF, Bugulma), O.V. Denisov (Tatneft PJSC, RF, Almetyevsk), A.V. Chirikin (Tatneft PJSC, RF, Almetyevsk)

The article presents the software tool for long-term investment planning for effective development of oil fields created by specialists of the Almetyevsk State Oil Institute, the TatNIPIneft, the Information Technology Center of Tatneft PJSC. Predictive planning of production enhancement operations is carried out on the basis of fields proxy models using highly efficient optimization algorithms and machine learning to form a long-term production program for events under resource constraints. Possibilities of using neural network approaches in solving the issue of clustering the performance indicators of planned measures distributed over the years to reduce the dimension of the optimization problem are considered in development of these tools. Comparative characteristics of the used optimization methods are included. Automated generation of many scenarios of the oil fields development is performed on proxy models of the workstation of the geologist LAZURIT with the calculation of technical and economic indicators of the planned production enhancement operations. Drilling of vertical and horizontal wells, sidetrack, transfer of wells to another horizon, the use of technology for dual completion and production, fracturing are considered as production enhancement operations. The results are used as an input for the system of long-term production program formation, which allows one to choose the most effective set of measures that meet the specified macro/microeconomic and resource constraints using the package of neural network and optimization algorithms. At the same time, the distribution of additional production from operations for a period of up to five years is taken into account, and a multi-scenario assessment of measure sets takes place within each annual planning period.

References

1. Denisov O.V., Application of optimization and network algorithms for effective portfolio of geological and technological activities formation of an oil company (In Russ.), Neftyanaya provintsiya, 2019, no. 1(17), pp. 90–101.

2. Zvezdin E.Yu., Mannapov M.I., Nasybullin A.V. et al., Stage-wise optimization of project well pattern using oil reserves evaluation program module (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2019, no. 7, pp. 28–31.

3. Certificate of authorship no. 2009616218 RF, Avtomatizirovannoe rabochee mesto geologa “LAZURIT” (Automated workplace of geologist “LAZURIT”), Authors: Akhmetzyanov R.R., Ibatullin R.R., Latifullin F.M., Nasybullin A.V., Smirnov S.V.

4. Certificate of authorship no. 2018611091 RF, KIM Ekspert (Complex for hierarchical modeling “Ekspert”), Authors: Sakhabutdinov R.Z., Ganiev B.G., Nasybullin A.V., Latifullin F.M., Sattarov Ram.Z., Smirnov S.V., Sharifullina M.A.

5. Nasybullin A.V., Latifullin F.M., Razzhivin D.A. et al., Creation and commercial introduction of methods of oil deposits development management on the basis of computer-aided design technologies (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2007, no. 7, pp. 88–91.

6. Khisamov R.S., Ibatullin R.R., Abdulmazitov R.G. et al., Use of information technologies for perfection of system of Tatneft OAO deposits development and development control (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2006, no. 10, pp. 46–49.

7. Latifullin F.M., Sattarov Ram.Z., Sharifullina M.A., Application of lazurit workstation software package for geological and reservoir modeling and well intervention planning for Tatneft’s production assets (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2017, no. 6, pp. 40–43.

8. Sharifullina M.A., Butusov E.V., Development of hierarchical modelling software for reservoir simulation, field management and selection of appropriate well stimulation technologies (In Russ.), Neftyanaya provintsiya, 2017, no. 4, pp. 116–124, URL: http://docs.wixstatic.com/ugd/2e67f9_9c3ae734e23f48b3a6f0ec08ae79e9eb.pdf.

9. Ismagilov I.I., Molotov L.A., Katasev A.S. et al., Fuzzy neural network model for rules generating of the objects state determining in uncertainty, Helix, 2018, V. 8(6), pp. 4662–4667.

10. Mustafin A.N., Katasev A.S., Akhmetvaleev A.M., Petrosyants D.G., Using models of collective neural networks for classification of the input data applying simple voting, The Journal of Social Sciences Research, 2018, no. 5, pp. 333–339.

11. Katasev A.S., Neuro-fuzzy model of fuzzy rules formation for objects state evaluation in conditions of uncertainty, Computer research and modeling, 2019, V. 11, no. 3, pp. 477–492.

The article presents the software tool for long-term investment planning for effective development of oil fields created by specialists of the Almetyevsk State Oil Institute, the TatNIPIneft, the Information Technology Center of Tatneft PJSC. Predictive planning of production enhancement operations is carried out on the basis of fields proxy models using highly efficient optimization algorithms and machine learning to form a long-term production program for events under resource constraints. Possibilities of using neural network approaches in solving the issue of clustering the performance indicators of planned measures distributed over the years to reduce the dimension of the optimization problem are considered in development of these tools. Comparative characteristics of the used optimization methods are included. Automated generation of many scenarios of the oil fields development is performed on proxy models of the workstation of the geologist LAZURIT with the calculation of technical and economic indicators of the planned production enhancement operations. Drilling of vertical and horizontal wells, sidetrack, transfer of wells to another horizon, the use of technology for dual completion and production, fracturing are considered as production enhancement operations. The results are used as an input for the system of long-term production program formation, which allows one to choose the most effective set of measures that meet the specified macro/microeconomic and resource constraints using the package of neural network and optimization algorithms. At the same time, the distribution of additional production from operations for a period of up to five years is taken into account, and a multi-scenario assessment of measure sets takes place within each annual planning period.

References

1. Denisov O.V., Application of optimization and network algorithms for effective portfolio of geological and technological activities formation of an oil company (In Russ.), Neftyanaya provintsiya, 2019, no. 1(17), pp. 90–101.

2. Zvezdin E.Yu., Mannapov M.I., Nasybullin A.V. et al., Stage-wise optimization of project well pattern using oil reserves evaluation program module (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2019, no. 7, pp. 28–31.

3. Certificate of authorship no. 2009616218 RF, Avtomatizirovannoe rabochee mesto geologa “LAZURIT” (Automated workplace of geologist “LAZURIT”), Authors: Akhmetzyanov R.R., Ibatullin R.R., Latifullin F.M., Nasybullin A.V., Smirnov S.V.

4. Certificate of authorship no. 2018611091 RF, KIM Ekspert (Complex for hierarchical modeling “Ekspert”), Authors: Sakhabutdinov R.Z., Ganiev B.G., Nasybullin A.V., Latifullin F.M., Sattarov Ram.Z., Smirnov S.V., Sharifullina M.A.

5. Nasybullin A.V., Latifullin F.M., Razzhivin D.A. et al., Creation and commercial introduction of methods of oil deposits development management on the basis of computer-aided design technologies (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2007, no. 7, pp. 88–91.

6. Khisamov R.S., Ibatullin R.R., Abdulmazitov R.G. et al., Use of information technologies for perfection of system of Tatneft OAO deposits development and development control (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2006, no. 10, pp. 46–49.

7. Latifullin F.M., Sattarov Ram.Z., Sharifullina M.A., Application of lazurit workstation software package for geological and reservoir modeling and well intervention planning for Tatneft’s production assets (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2017, no. 6, pp. 40–43.

8. Sharifullina M.A., Butusov E.V., Development of hierarchical modelling software for reservoir simulation, field management and selection of appropriate well stimulation technologies (In Russ.), Neftyanaya provintsiya, 2017, no. 4, pp. 116–124, URL: http://docs.wixstatic.com/ugd/2e67f9_9c3ae734e23f48b3a6f0ec08ae79e9eb.pdf.

9. Ismagilov I.I., Molotov L.A., Katasev A.S. et al., Fuzzy neural network model for rules generating of the objects state determining in uncertainty, Helix, 2018, V. 8(6), pp. 4662–4667.

10. Mustafin A.N., Katasev A.S., Akhmetvaleev A.M., Petrosyants D.G., Using models of collective neural networks for classification of the input data applying simple voting, The Journal of Social Sciences Research, 2018, no. 5, pp. 333–339.

11. Katasev A.S., Neuro-fuzzy model of fuzzy rules formation for objects state evaluation in conditions of uncertainty, Computer research and modeling, 2019, V. 11, no. 3, pp. 477–492.


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