A Methodology to Integrate Multiple Simulation Models and 4D Seismic Data Considering Their Uncertainties
- Germano S. C. Assunção (State University of Campinas) | Alessandra Davolio (State University of Campinas) | Denis J. Schiozer (State University of Campinas)
- Document ID
- Society of Petroleum Engineers
- SPE Annual Technical Conference and Exhibition, 26-28 September, Dubai, UAE
- Publication Date
- Document Type
- Conference Paper
- 2016. Society of Petroleum Engineers
- 5.1.8 Seismic Modelling, 7.6 Information Management and Systems, 5.5.5 Evaluation of uncertainties, 5.5.8 History Matching, 5 Reservoir Desciption & Dynamics, 5.1.9 Four-Dimensional and Four-Component Seismic, 5.5 Reservoir Simulation, 5.6.3 Deterministic Methods, 5.1.7 Seismic Processing and Interpretation, 5.1 Reservoir Characterisation, 7 Management and Information
- History Matching, Probabilistic Integration, Reservoir Monitoring, 4D Seismic, Reservoir Simulation
- 0 in the last 30 days
- 146 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 8.50|
|SPE Non-Member Price:||USD 25.00|
Traditionally, integration between 4D seismic (4DS) and simulation data has been performed considering the 4DS data deterministically. However, there are uncertainties in the response of seismic. The goal of the methodology presented in this work is to compare the changes of dynamic properties estimated from 4DS and simulation models considering the uncertainties inherent to both data.
The relevant reservoir uncertainties can be combined to generate multiple simulation models, which provide maps of dynamic changes, such as pressure change (?p) and water saturation variation (?Sw). Available 4DS can also be used to map dynamic changes. Through a stochastic seismic inversion, multiple ?Sw and ?p maps can be obtained from 4DS. After selecting a proper scale (scale transference), we compare the dynamic maps from seismic and simulation data using probabilistic density functions (PDFs), establishing levels of agreement/disagreement between 4DS and simulation data.
To validate the methodology we use a synthetic dataset, with moderate complexity and seven uncertainties mapped, such as fault transmissibility, porosity, facies, and permeability. 500 maps of ?Sw and ?p from 4D seismic were generated from prior probabilistic seismic inversion. 500 simulation models previously calibrated using well production data generated the set of 500 maps of ?Sw and ?p from simulation. Applying the methodology, we identify four regions: (1) reservoir locations where both estimates (seismic and simulation) are similar, showing regions properly calibrated, (2) locations where simulation estimates are more precise than 4D seismic, (3) reservoir locations where the data sets indicate divergent estimates, and (4) 4DS estimates are more precise than simulation.
This information can be very useful to guide data integration. As an example, we show that region (4) can be used to select the simulation models that reproduce ?Sw or ?p behavior from 4DS, since 4D seismic data is more precise than the simulation estimates in this region. Other useful information from the proposed methodology is that the reservoir zones identified as region (2) can be used as a constraint to reinterpret 4D seismic data, as simulation estimates are more precise.
The methodology is a new way to evaluate the information from 4D seismic and simulation data considering uncertainties. The identification of these four regions can be useful in the parametrization phase of the history matching procedure (a complex process), as an additional tool to understand the properties in this procedure. The methodology also indicates possible locations to use reservoir engineering constraints to improve seismic interpretation, in regions where estimates from simulation are more precise than 4D seismic data. Moreover, we can use the methodology to determine critical reservoir locations to be reevaluated, those presenting disagreement between the two data source.
|File Size||10 MB||Number of Pages||16|