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Algorithm of structure uncertainty calculation for fields at the exploration stage

UDK: 550.834.05
DOI: 10.24887/0028-2448-2019-12-26-29
Key words: uncertainty, structural interpretation, seismic, standard deviation
Authors: M.A. Kuntsevich (Gazpromneft NTC LLC, RF, Saint-Petersburg), A.S. Goncharov (Gazpromneft NTC LLC, RF, Saint-Petersburg), S.A. Nekhaev (Gazpromneft NTC LLC, RF, Saint-Petersburg)

At the stage of transition from deterministic estimates of reserves and resources to probabilistic models, geologists face challenges of estimation and analysis of the uncertainty that exist at different stages of geological modeling. For the hydrocarbon fields at the exploration stage, the key uncertainty is the structural model, as one of the factors that maximally affects the estimated reserves and resources. Most often, the basis for structural constructions is 2D or 3D seismic data, the interpretation quality of which has a significant impact on the output data, and, as a result, common uncertainty of seismic data. The quality of the data, the limitations of the method, and the subjectivity of interpreters make the results of seismic interpretation controversial, which makes the task of estimating the error/uncertainty of seismic data one of the most important stage, which goes as the basis for creating stochastic geological models in the probabilistic geological modeling process. The accuracy of seismic data can be described as the integration of the time correlation error associated with the reflecting horizon, and the error of the velocity model – the function of the translation of the interpretation results into the depth domain. The authors propose an algorithm for estimating structural uncertainty for fields at the exploration stage, using all the main factors affecting to the seismic interpretation outputs. The results of a quantitative assessment of structural construction uncertainty is a standard deviation map, which goes as the basis for creating stochastic geological models in the probabilistic geological modeling process, further IIP estimation and the sensitivity analysis of key uncertainties.

References

1. Levyant V.B., Ampilov Yu.P., Glogovskiy V.M. et al., Metodicheskie rekomendatsii po ispol'zovaniyu dannykh seysmorazvedki (2D, 3D) dlya podscheta zapasov nefti i gaza (Guidelines for using seismic data (2D, 3D) for calculating oil and gas reserves), Moscow: Publ. of Central Geophysical Expedition, 2006, 40 p.

2. Kiselev V.S. et al., Instruktsiya po otsenke kachestva strukturnykh postroeniy i nadezhnosti vyyavlennykh i podgotovlennykh ob"ektov po dannym seysmorazvedki MOV-OGT (pri rabotakh na neft' i gaz) (Instruction for assessing the quality of structural structures and reliability of identified and prepared objects based on seismic data of CDP seismic reflection method (for oil and gas works)), Moscow: Publ. of VNIIGeofizika, 1984.

3. Averbukh A.G., Ivanova N.L., Quantification and results assessment for 3D seismic-based mapping errors (In Russ.), Ekspozitsiya Neft' Gaz, 2009, no. 3, pp. 61–62.

4. Pinto V.R. et al., Seismic uncertainty estimation in reservoir structural modelling, Firstbreak, 2017, October, V. 35, pp. 2986–2990, DOI: 10.1190/segam2016-13953669.1.

5. Thore P., Shtuka A., Structural uncertainties: Determination, management, and applications, Geophysics, 2002, V. 67 (2).

At the stage of transition from deterministic estimates of reserves and resources to probabilistic models, geologists face challenges of estimation and analysis of the uncertainty that exist at different stages of geological modeling. For the hydrocarbon fields at the exploration stage, the key uncertainty is the structural model, as one of the factors that maximally affects the estimated reserves and resources. Most often, the basis for structural constructions is 2D or 3D seismic data, the interpretation quality of which has a significant impact on the output data, and, as a result, common uncertainty of seismic data. The quality of the data, the limitations of the method, and the subjectivity of interpreters make the results of seismic interpretation controversial, which makes the task of estimating the error/uncertainty of seismic data one of the most important stage, which goes as the basis for creating stochastic geological models in the probabilistic geological modeling process. The accuracy of seismic data can be described as the integration of the time correlation error associated with the reflecting horizon, and the error of the velocity model – the function of the translation of the interpretation results into the depth domain. The authors propose an algorithm for estimating structural uncertainty for fields at the exploration stage, using all the main factors affecting to the seismic interpretation outputs. The results of a quantitative assessment of structural construction uncertainty is a standard deviation map, which goes as the basis for creating stochastic geological models in the probabilistic geological modeling process, further IIP estimation and the sensitivity analysis of key uncertainties.

References

1. Levyant V.B., Ampilov Yu.P., Glogovskiy V.M. et al., Metodicheskie rekomendatsii po ispol'zovaniyu dannykh seysmorazvedki (2D, 3D) dlya podscheta zapasov nefti i gaza (Guidelines for using seismic data (2D, 3D) for calculating oil and gas reserves), Moscow: Publ. of Central Geophysical Expedition, 2006, 40 p.

2. Kiselev V.S. et al., Instruktsiya po otsenke kachestva strukturnykh postroeniy i nadezhnosti vyyavlennykh i podgotovlennykh ob"ektov po dannym seysmorazvedki MOV-OGT (pri rabotakh na neft' i gaz) (Instruction for assessing the quality of structural structures and reliability of identified and prepared objects based on seismic data of CDP seismic reflection method (for oil and gas works)), Moscow: Publ. of VNIIGeofizika, 1984.

3. Averbukh A.G., Ivanova N.L., Quantification and results assessment for 3D seismic-based mapping errors (In Russ.), Ekspozitsiya Neft' Gaz, 2009, no. 3, pp. 61–62.

4. Pinto V.R. et al., Seismic uncertainty estimation in reservoir structural modelling, Firstbreak, 2017, October, V. 35, pp. 2986–2990, DOI: 10.1190/segam2016-13953669.1.

5. Thore P., Shtuka A., Structural uncertainties: Determination, management, and applications, Geophysics, 2002, V. 67 (2).



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