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The economic consequence of exploitation in areas with an unspecified risk of abnormal pressure profiles range from increased drilling costs to unrealised prospect potential. Optimised planning practices will impact on not only the costs of drilling but also on the quality of the reservoir evaluation and productivity assessment.Numerous exploratory wells in the Carnarvon Basin have encountered unprognosed high pore pressures in the past, resulting in increased concerns about well control and safety, and as a consequence higher drilling costs. High pressures encountered at Parker–1ST1, Forrest–1AST1, Venture–1ST1, and Venture–2ST1, in particular, caused a high level of concern for moderately deep drilling targets. As a result of the diversity of potential overpressure mechanisms, there is a variety of opinion on the risk of encountering abnormal pressure in particular areas, and no standard way to capture and incorporate this information into planning and drilling decisions.At the end of 1999 a project was defined to evaluate the risk of overpressure of a prospect in this area. This project had the primary focus of evaluating the risk of encountering high pore pressures when drilling an exploratory well. This risk assessment was directed towards a decision point for well design, which had cost implications in anticipation of drillingIn the process of technical assessment of abnormal pressure in this prospect, it was important to include all of the necessary data and technical practices, which could contribute to an understanding of the prediction. The application of a cooperative multi-functional team and a software infrastructure (Juniper) was instrumental in allowing this process to take place. A visual decision tree with risk assessment allowed for input from all contributors and for the inter-relationship of the inputs. This comprised the methodology for assessment.The methodology highlighted, explicitly, areas of high uncertainty where evidence neither for nor against overpressure was available. These areas became the focus of technical work, as they had potential for significant impact on the risk assessment. A sub-team extensively reviewed the pressure tests, sonic logs, borehole influxes and mud weights of nearby wells. The results of the well study had a bearing on the choice of analogue, the geological model, and pressure prediction. A geological modelling sub-process was carried out to test the significance of compaction disequilibrium, organic maturation and permeability on overpressure generation. A geophysical sub-process was initiated to complement the pressure modelling risk element. Surface seismic data was depth processed to relate velocities to trends obtained from the well study.The methodology was found to be a highly effective technique for recording the decision processes and as a tool for interdisciplinary communication in a cooperative and non-threatening environment. The outcome of the study was to highlight reduced risk of overpressure in the prospect as perceived by all parties (geoscientists, drilling engineers, management and joint venture parties). The common view on risk prompted a reassessment of the risk profiles on all the related wells in the program and allowed revision of the drilling programs and significant cost savings relative to the original forecasts for the program.

TX 75083-3836, U.S.A., fax 01-972-952-9435. 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.