The studied reservoir consists of turbiditic slope channels which form elongated sandy bodies with dimension of 4 to 12 Km in length and 1 to 4 Km in width. The thickness is varying from few metres to almost one hundred. These channels are hydraulically separated and characterized by high values of porosity and permeability. These sand bodies were identified and porosity characterized by means of seismic data. The first three wells have proved the correlation between gas-bearing sands and "low-impedance" seismic responses. Nevertheless, since those wells did not cross all the sand bodies (only 6 out of 14) the main problem at that stage was the risk assessment of the hydrocarbon occurrence in the remaining bodies. In order to assess this risk the first approach was to identify, for all the bodies, relevant seismic criteria (Amplitude strength, Signal noisiness, Fragmentation and Recon AVO) to use for a qualitative evaluation defining a ranking of the undrilled bodies. The following step was to apply a Bayesian approach to assess the relevant probability of hydrocarbon occurrence. This technique requires the estimation of two parameters: prior probability based on geological area knowledge and likelihood derived from seismic indicators. On the base of the probability ranking a limited number of scenarios was defined. For each scenario a dedicated plan of development was assigned. A new appraisal well was drilled after this evaluation. This allowed verifying the validity of the ranking system used to estimate probability of success with regards to the undrilled segments. The results show good agreement between seismic data and well's results with one (positive) exception. Moreover a traditional "Risk Analysis" was performed in perforated bodies to sample all the critical parameters (static and dynamic) and to build several models. By these models a set of volumetrics and production profiles were obtained.

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TX 75083-3836, U.S.A., fax +1-972-952-9435 In exploration plays driven by DHI, seismic thin beds are common targets. When resolution capabilities are comparable to isochrones of remarkable elastic contrasts, reflections tend to fall around tuning thickness, where interference phenomena prevent a correct calibration of amplitudes to reservoir properties. If a de-tuning step is not applied in seismic characterization, wrong estimation of reservoir properties and pay thickness may lead to inaccurate volumetrics and misleading geologic models. These issues were faced in the characterization of a Kutei Basin (Offshore Kalimantan, Indonesia) discovery, where gas sands, acoustically marked by lower P-impedance than bounding shales, respond as bright, single-loop reflections (i.e. seismic thin beds). In order to support appraisal and reservoir modeling activities, our seismic characterization approach combined the following steps: a) Statistical tuning charts realization by extracting reservoir isochron and amplitude; b) Investigation of petro-elastic relations through rock physics modeling; c) Definition of deterministic tuning curves by generating a family of pseudo-reservoir responses via forward seismic modeling and d) De-tuned calibration of amplitude -isochron pairs to Porosity*Thickness (PT) and Net Pay. Appraisal wells confirmed the reliability of this approach but also revealed how other uncertainties may impact reservoir quality predictions. For this reason, PT realizations were only used as "soft" information in the reservoir model, built through a Sequential Indicator Simulation of sedimentological facies recognized in cores. Assuming a link between seismic porosity and facies, normalized porosity maps derived from PT estimates were used to condition the horizontal facies distributions and define a seismic-consistent variography. Sensitivity analysis confirmed the robustness of the approach and final results appear consistent with the de-tuned PT predictions. In a field where seismic thin beds affected by tuning represent the key geophysical issue to address, the applied workflow ensured the link between geophysics and geological modeling, from assessment of gas in-place to dynamic simulation.