Publications

Multi point statistics applied to a deltaic environment: a case study in the Upper-Miocene formation, Peciko Field, Mahakam area

Proceedings Title : Proc. Indon. Petrol. Assoc., 39th Ann. Conv., 2015

Peciko is an offshore gas field located to the south of the Mahakam delta. The sedimentary column is composed of a stacking of deltaic sequences. The 4th order sequence of interest belongs to the Upper Miocene formation. The reservoirs are essentially constituted of distributary channels from the delta plain. In this sequence, seismic data are too poor to interpret the fairway limits. Consequently, the deterministic design of fairway based only on well data is highly uncertain. To reduce the uncertainty on the fairways interpretation, a stochastic method was performed, viz. Multi Point Statistics (MPS). As a stochastic method, MPS allows us to construct rapidly several scenarios. This method was chosen because it combines the benefits of a pixel-based method (honoring perfectly hard data) and an object-based method (reproducing shapes of object). The influence of uncertainties such as the percentage and direction of fairways on the Initial Gas in Place was tested. The aim was to assess the impact of these parameters on the spatial repartition of fairways in the gas pool. As a result, the distribution of IGIP by fairway scenario is assessed showing that the percentage of fairways in the gas pool remains quite stable. In addition to that, a main direction of fairway was highlighted with the identification of a secondary direction. Through this method, the connectivity of each fairway scenario was evaluated. The integration of a workflow to the method allowed the construction of scenario avoiding disconnected fairways at wells. Thus, this static study could be used for dynamic simulations. Finally, the multi-scenario approach allowed the computation of probability maps of fairway occurrence. These maps are interesting outside well area where they show the most probable location of fairways which can be useful for the identification of sweet spots.

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