Objectives and scope of the Study In this paper a new approach is presented to consistently integrate basin-scale information into reservoir models. The impact of the quantitative integration of boundary conditions derived from basin-scale modeling on the facies distribution at the reservoir scale is evaluated. To this purpose, a new workflow was defined based on a geostatistical approach. The aim was that of integrating the typical dataset for reservoir geological modeling, comprising well and seismic data, with a potentially new kind of data obtained from 3-D process-based stratigraphic modeling and related to the distribution of the hydrocarbon bearing volumes. Quantitative coherence between the small scale reservoir volume and the large-scale geological setting defined by the basin model was imposed. Synthetic case studies were set up to verify the effectiveness of the method. Applications The entire process was applied to a fluvio-deltaic environment to integrate the basin-derived information, such as (1) the overall reservoir/non reservoir volumes, (2) the 3D distribution of channelized volumes and (3) related flow directions, to the reservoir model. Eventually, the uncertainty reduction in the description of the final facies distribution at the reservoir scale was evaluated. Results, Observations and Conclusions The developed approach proved very efficient to estimate the lithological fraction of the hydrocarbon bearing rocks (i.e. sands in a shaley/clayey environment). The lithological fraction is of crucial importance during the appraisal phase of a reservoir when relevant decisions have to be taken but few wells are drilled and, as a consequence, a limited amount of data is available to perform a reliable volumetric estimate. Furthermore, the prediction of the 3D facies architecture (such as the channel pattern in a fluvial depositional environment) can effectively assist in the well planning strategy. Besides, the overall uncertainty affecting a reservoir model can be assessed; this uncertainty is both a function of the initial environmental parameters for basin modeling and of the adopted methodological approach for basin-to-reservoir data integration. Therefore, an accurate inference of the basin parameters is needed to achieve a reliable prediction of both the channel location and the sand/shales volumes fractions. Significance of subject matter Reservoir modeling can significantly benefit from the integration of quantitative basin-scale information. In particular, the numerical modeling of the stratigraphic sequence can be used to steer the reconstruction of the reservoir internal geometry and to reduce the uncertainty in the distribution of the hydrocarbon-bearing lithologies. Furthermore, this approach provides a rigorous assessment of the information content of all the available data and thus it might be very useful to guide further data acquisition campaigns.

How to integrate basin-scale information into reservoir models / Sacchi, QUINTO RENATO; Weltje, G. J.; SALINA BORELLO, Eloisa. - (2013). (Intervento presentato al convegno EAGE Annual Conference & Exhibition incorporating SPE Europec tenutosi a London, UK nel 10-13 June) [10.2118/164830-MS].

How to integrate basin-scale information into reservoir models

SACCHI, QUINTO RENATO;SALINA BORELLO, ELOISA
2013

Abstract

Objectives and scope of the Study In this paper a new approach is presented to consistently integrate basin-scale information into reservoir models. The impact of the quantitative integration of boundary conditions derived from basin-scale modeling on the facies distribution at the reservoir scale is evaluated. To this purpose, a new workflow was defined based on a geostatistical approach. The aim was that of integrating the typical dataset for reservoir geological modeling, comprising well and seismic data, with a potentially new kind of data obtained from 3-D process-based stratigraphic modeling and related to the distribution of the hydrocarbon bearing volumes. Quantitative coherence between the small scale reservoir volume and the large-scale geological setting defined by the basin model was imposed. Synthetic case studies were set up to verify the effectiveness of the method. Applications The entire process was applied to a fluvio-deltaic environment to integrate the basin-derived information, such as (1) the overall reservoir/non reservoir volumes, (2) the 3D distribution of channelized volumes and (3) related flow directions, to the reservoir model. Eventually, the uncertainty reduction in the description of the final facies distribution at the reservoir scale was evaluated. Results, Observations and Conclusions The developed approach proved very efficient to estimate the lithological fraction of the hydrocarbon bearing rocks (i.e. sands in a shaley/clayey environment). The lithological fraction is of crucial importance during the appraisal phase of a reservoir when relevant decisions have to be taken but few wells are drilled and, as a consequence, a limited amount of data is available to perform a reliable volumetric estimate. Furthermore, the prediction of the 3D facies architecture (such as the channel pattern in a fluvial depositional environment) can effectively assist in the well planning strategy. Besides, the overall uncertainty affecting a reservoir model can be assessed; this uncertainty is both a function of the initial environmental parameters for basin modeling and of the adopted methodological approach for basin-to-reservoir data integration. Therefore, an accurate inference of the basin parameters is needed to achieve a reliable prediction of both the channel location and the sand/shales volumes fractions. Significance of subject matter Reservoir modeling can significantly benefit from the integration of quantitative basin-scale information. In particular, the numerical modeling of the stratigraphic sequence can be used to steer the reconstruction of the reservoir internal geometry and to reduce the uncertainty in the distribution of the hydrocarbon-bearing lithologies. Furthermore, this approach provides a rigorous assessment of the information content of all the available data and thus it might be very useful to guide further data acquisition campaigns.
2013
9781613992548
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2594957
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