New seismic data types and new interpretation tools are rapidly changing and expanding the applicability of seismic methods. In Australia, the hydrocarbon and mining industries are both using an increased proportion of 3D seismic data to improve lateral predictability and to reduce exploration and production risks and costs. New techniques and workflows described below are expected to come into more common usage over the next five years.3D reservoir characterisation workflows integrate all reservoir data types including well log measurements, seismic data, reservoir models and simulations. Within the domain of seismic data, complementary data types, such as 3D, 4D, 4C, AVO and down-hole seismic, need to be synthesised into a single optimum reservoir representation. One way of producing such results is by using seismic classification which is based on a set of geostatistical and neural network algorithms to produce a single class map or cube mapping reservoir parameters with an uncertainty estimate associated with each trace and sample location.Seismic classification is applied to two types of seismic data: attribute grids and 3D seismic attribute cubes. Seismic classification provides a tool for generalised inversion of seismic data for lithofacies, faults and fluids (DHI, Direct Hydrocarbon Indicators). At the acquisition and processing stages of seismic data, the same classification algorithms are used to assess data quality to quantify and improve seismic data quality.Recent developments in seismic attributes have shown that additional reservoir characterisation information is obtained by decomposing the seismic trace into a set of polynomial coefficients. Such seismic attributes are computed both on the seismic trace and on a synthetic trace computed along the borehole trajectory in order to calibrate the seismic attribute by measured reservoir parameters.An increasing number of 3D attribute cubes or transforms of the raw seismic volume are used by geophysicists to better capture lateral changes in seismic response. The potential and pitfalls of 3D attribute cubes are illustrated with reference to Australasian examples.Increasing interest is also being shown in fault and fracture mapping bom seismic data with applications in both the mining and hydrocarbon industries. Fault mapping and automated extraction can both be based on structural seismic attribute grids and cubes.
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AbstractImproved oil recovery on mature fields relies on a reservoir model accurate enough to identify by-passed oil and to monitor fluid responses to production. Integration of seismic 3D volumes with stochastic realisations and flow simulations in a single interpretation environment (Shared Earth Model) allows asset teams to perform rapid seamless iterations leading to a perfected representation of the reservoir (Fig. 1). Facies, fault and fluid mapping from 3D/4D/4C seismic data has moved one large step ahead with the advent of grid-based and 3D volume seismic classification (Fig. 2). Resulting deterministic spatial probability estimates of reservoir parameters are direct inputs to the reservoir model to constrain large uncertainties present in geostatistical distribution of reservoir parameters.
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