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Geological modelling: characterization of fluvial sediments and hanging wall traps

Objective

To develop modelling techniques for use in both oil exploration and development work. Goals comprise two complementary parts: 1) to quantify uncertainties in reservoir geometry of fluvial sediments by stochastic modelling, 2) to develop interactive sequential forward modelling software for the investigation and delineation of potential and actual hanging wall traps.

The efficient development and exploitation of oil and gas accumulations is to a large extent determined by the detailed knowledge of the reservoir geometry and the spatial distribution of permeability within the reservoir. Deterministic and stochastic computer modelling are tools to reduce reservoir uncertainties.

Computer modelling of reservoir parameters requires the input of detailed geological information from seismic and wells, from analog reservoirs elsewhere or, preferably, from well-documented outcrops of similar formations. By varying the input parameters a limited number of reservoir models is generated, which are subsequently validated through matching with the geological model.

The project focuses on the computer modelling of two types of reservoir heterogeneity: 1) in fluvial sediments, and 2) related to potential hanging wall traps.

Both project parts will be carried out in four main phases:

1) Data acquisition: comprises outcrop studies in the Tertiary Loranca Basin, central Spain (fluvial), and seismic and well data from North and Central North sea, Celtic Sea and porcupine Basin, onshore U.K. (hanging wall).

2) Data processing: includes petrographical and geostatistical techniques (fluvial), quantitative analysis of fault geometries (hanging wall).

3) Computer modelling: stochastic modelling of processed geological data will include the construction of synthetic logs and cross-sections (fluvial), and of combined numerical models of fault-associated stratigraphy (hanging wall).

4) Evaluation: towards the end of a data acquisition-processing-modelling sequence the results of the modelling effort will be evaluated in terms of type of the data used during the execution of the modelling, and the results will be tested on available data sets.

Coordinator

Technische Universiteit Delft
Address
120,Mijnbouwstraat 120
2600 GA Delft
Netherlands

Participants (5)

Business Unit of TNO Built Environment and Geosciences
Netherlands
Address
Van Mourik Broekmanweg 6
2628 XE Delft
CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS
Spain
Address
Calle Serrano 117
Madrid
THE UNIVERSITY OF LIVERPOOL
United Kingdom
Address
Senate House, Abercromby Square
L69 3SG Liverpool
UNIVERSITY COLLEGE DUBLIN
Ireland
Address
Belfield
4 Dublin
UNIVERSITY OF AARHUS
Denmark
Address
1,Nordre Ringgade 1-3
8000 Aarhus C