The structure is one of the main parameters that significantly influences the reserves at additional exploration of poorly studied deep horizons of complex deposits. The results of seismic interpretation, the quality of which is affected by each stage of seismic work, are the basis for the structural framework. For deep horizons the seismic error increases, that makes the problem of taking into account the structure variation is relevant.
In this article the methodology for estimating structural uncertainty from seismic and well data is described using the example of the unique offshore oil, gas and condensate field in the Azerbaijan sector of the Caspian Sea, which is characterized by an extremely complex tectonic structure.
The deposit is associated to a ridge of anticlines of the South Caspian oil and gas basin. The target interval is deep-lying horizons of the underexplored lower interval, penetrated by only a few exploration wells on an area of more than 1000 km2. The pool altitude reaches 1,5 km, which caused a spread in the assessment of reserves of more than 50%. The uncertainty assessment of the structure was based on seismic volumes, VSP and well data.
In the process of work, a methodology has been developed that takes into account the errors in data processing, velocity model and interpretation of seismic data. The uncertainty maps are obtained differentially, then combined and taken into account at the stage of constructing the multivariate structural model.
To reduce errors in the lower interval, the data of the upper production interval were involved, the structural model of the target horizons was constructed by adding thickness maps to the reference surface taking uncertainties into account. The seismic interpretation of the upper, high-drilled production interval, located above the target at 250-1000 m, and the use of information on production wells in the upper layers, reduced the structural uncertainty for the target horizons of the lower interval by more than 2.5 times.
The analysis of uncertainties has shown that the quality of the resulting surfaces is strongly influenced by the velocity model, where the main error comes at the expense of horizons above the target interval. Using upper layers well data, construction of a structural model by adding thicknesses to the reference surface with the transformation depth errors in the thickness errors, made it possible to significantly reduce the error in the velocity model, which in turn reduced the uncertainty of the structure of deep low-drilled horizons and reduced the variance in the amount of reserves under probabilistic estimation.
As a result, was developed methodology for estimating the structural uncertainty for poor investigated deep deposits based on the differentially obtained data errors used in the interpretation. The application of this approach in additional exploration of deep reservoirs with a complex tectonic structure has allowed to reduce the spread of reserves with a probabilistic estimate of more than 20%, reliably predict the efficiency of field development and reduce risks in making reservoir management decisions.