Earth models for early exploration stages
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1 ANNUAL MEETING MASTER OF PETROLEUM ENGINEERING Earth models for early exploration stages Ângela Pereira PhD student 3/May/2016 Instituto Superior Técnico 1
2 Outline Motivation Methodology Case Study Seismic inversion results Conclusions 3/May/2016 Instituto Superior Técnico 2
3 Motivation Prospect characterization and uncertainty assessment of unexplored areas or in early stages of exploration. How? Combination of information from Geological analogs and Geophysical data in a geoestatistical seismic inversion procedure. ENMC ENMC 3/May/2016 Instituto Superior Técnico 3
4 Methodology Geostatistical Seismic Inversion algorithm - GSI (Soares et al. 2007; Caetano, 2009)). Use of geological analogs for extraction of a priori distributions of Acoustic Impedance (AI) (e.g. well-logs from nearby wells). Use of a geological conceptual model based on seismic interpretation. 3/May/2016 Instituto Superior Técnico 4
5 Geostatistical Seismic Inversion - GSI Global approaches (Soares et al., 2007; Caetano, 2009) i. Generation and perturbation of entire cube of parameters (acoustic properties). ii. Optimization method (genetic algorithms) to assure the convergence of the iterative procedure. 3/May/2016 Instituto Superior Técnico 5
6 Geological analogs Regional Geology Geological Analogs (wells-logs from nearby wells) Dt Rhob AI GEOLOGICAL MODEL Seismic Interpretation Acoustic Impedance distributions extracted from geological analogs The distributions of AI should be representative of the expected lithofacies and also of the relation between the different litho-stratigraphic units. 3/May/2016 Instituto Superior Técnico 6
7 Geological model SEISMIC SEISMIC INTERPRETATION DEFINITION OF GEOLOGICAL MODEL GEOLOGICAL ZONES Zone 1 Zone 2 Zone 3 Geological model with 3 different lithofacies based on seismic interpretation Grid size: 198 x 279 x 190 3/May/2016 Instituto Superior Técnico 7
8 Geological analogs Acoustic Impedance - AI Each a priori AI distribution, for the different geological zones were extracted directly from geological analogs (well-logs from nearby wells). They correspond to the expected lithofacies for each zone. GEOLOGICAL ANALOGS (nearby appraisal well) Dt Rhob AI A PRIORI DISTRIBUTION OF ACOUSTIC IMPEDANCE (AI) sands with shales shales marls GEOLOGICAL MODEL AI Zone 1 Zone 2 Zone 3 3/May/2016 Instituto Superior Técnico 8
9 Methodology Workflow Geological model Stochastic Simulation of AI (DSS) N(AI) Convolution * Synthetic Compare seismic Seismic Forward model Local correlation coefficient calculation and Selection of best fit models AI distributions extracted from geological analogs Use best models as secondary variable for co-simulation. Iterate until the convergence of the method. Best AI model Best local correlation coef. 3/May/2016 Instituto Superior Técnico 9
10 Case study The methodology proposed was applied to an unexplored area, where the potential reservoir is expected to be in a turbidite system. 3D post-stack seismic volume, with sampling interval 2ms 3 appraisal wells outside the area used as analogs (w1, w2, w3) 3/May/2016 Instituto Superior Técnico 10
11 Case study Well-logs available: Sonic, Density, Acoustic Impedance (computed from Sonic and Density logs) Well-logs used as analogs Dt Rhob AI Dt Rhob AI Dt Rhob AI 3/May/2016 Instituto Superior Técnico 11
12 Seismic Inversion Parameterization Geological model with 3 lithofacies zones Tree different a priori Acoustic Impedance (AI) distributions extracted from the geological analogs. Spatial continuity pattern expressed by a variogram model obtained from seismic data. Statistical wavelet extracted from seismic data. The algorithm was run with 6 iterations in each one were generated 32 models of Acoustic Impedance. 3/May/2016 Instituto Superior Técnico 12
13 Evolution of Global Correlation Coefficient 3/May/2016 Instituto Superior Técnico 13
14 Correlation between real and synthetic seismic seismic REAL SEISMIC SYNTHETIC it#6 CC=0.85 synthetic it#6 3/May/2016 Instituto Superior Técnico 14
15 Seismic amplitude Difference in amplitude between real and synthetic seismic GEOLOGICAL MODEL REAL SEISMIC SYNTHETIC it#6 SEISMIC - SYNTHETIC Zone 1 Zone 2 Zone 3 Transition zones have higher diferences in amplitude 3/May/2016 Instituto Superior Técnico 15
16 Local Correlation Coefficient - CC REAL SEISMIC SYNTHETIC it#6 LOCAL CC it#6 1 BEST LOCAL CC it#6 0 3/May/2016 Instituto Superior Técnico 16
17 seismic Correlation between real and synthetic seismic Zone 2 Potential reservoir turbidite system GEOLOGICAL MODEL Zone 1 Zone 2 Zone 3 REAL SEISMIC HORIZON SLICE SEISMIC HORIZON SLICE SYNTHETIC it#6 CC=0.90 synthetic it#6 3/May/2016 Instituto Superior Técnico 17
18 Acoustic Impedance model A PRIORI DISTRIBUTION OF ACOUSTIC IMPEDANCE sands with shales shales marls Low acoustic impedance values correspond to high porosity areas GEOLOGICAL MODEL SIMULATED AI it#6 HORIZON SLICE BEST AI it#6 MEAN AI it#6 Zone 1 Zone 2 Zone 3 3/May/2016 Instituto Superior Técnico 18
19 Conclusions It is important that the acoustic impedance distributions extracted from geological analogs should be representative of the expected lithofacies and also of the relation between the different litho-stratigraphic units. The Geostatistical Seismic Inversion methodology using geological analogs proved to be a valuable tool to be applied on unexplored areas or in early stage of exploration for prediction of the subsurface geology and for prospect characterization. 3/May/2016 Instituto Superior Técnico 19
20 Acknowledgements Partex Oil and Gas and Repsol for allowing the use of the data and give permission to show the results. Schlumberger for the academic licenses of Petrel CGG for the academic licenses of Hampson-Russel software. Thank you 3/May/2016 Instituto Superior Técnico 20
21 References Caetano, H. [2009] Integration of Seismic Information in Reservoir Models: Global Stochastic Inversion, PhD thesis, Instituto Superior Técnico, University of Lisbon. Pereira A., Nunes R., Azevedo L., Guerreiro L. & Soares A. [2016] Seismic inversion using analogs for reservoir characterization and uncertainty assessment in early stages of exploration. Search and Discovery, Proccedings of International Conference and Exhibition AAPG/SEG 2016 (Accepted). Pereira A., Nunes R., Azevedo L., Guerreiro L. & Pereira M.J. [2015] Global Stochastic Inversion Using "Analogs-wells" and Zonal Distributions - Application to an Unexplored Area. Proceedings of EAGE 2015 Conference - Petroleum Geostatistics. Soares, A., Diet, J.D. & Guerreiro, L. [2007] Stochastic Inversion with a Global Perturbation Method, EAGE Conference on Petroleum Geostatistics, Extended Abstracts. 3/May/2016 Instituto Superior Técnico 21
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