--> From Seismic Interpretation to Reservoir Modeling of the Lunskoye Field, Offshore Sakhalin

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From Seismic Interpretation to Reservoir Modeling of the Lunskoye Field, Offshore Sakhalin

 

Ross, Liz1, Kevin King1, Enrique Carballido1, Patrick Jackson1, Gerard Bodewitz2, Greg Stone2, Hajo Van Hasselt2, Edwin Lamers2 (1) Sakhalin Energy Investment Co, Den Haag, Netherlands (2) Shell International Exploration and Production, Rijswijk, Netherlands

 

The Lunskoye Gas Field is the centrepiece of Sakhalin II development, one of Shell’s most strategic acquisitions of the last decade. The 18.2 TCF gas in place along with the Far East LNG market drive the timing and success of the entire project. The first LNG shipment is scheduled for 2007.

Following the acquisition of 3D-seismic data in 2003, building has commenced on a new generation of seismically-constrained models. There are many challenges, notwithstanding, imaging through a massive gas cloud, modelling of velocities, interpretation on PSTM and PSDM volumes, time to depth conversion, definition of a cross-discipline framework, along with data, software and discipline integration.

The new seismic survey was successful in undershooting the cause of the gas cloud. The PSTM and PSDM demonstrate, improved imaging over the crest and improved ampli­tude reliability in the reservoir, which will aid in rock property distribution. Comparisons will be made between both surveys, including orthogonal depth migrations, reservoir reflectivi­ty, amplitude and continuity.

In parallel to the seismic interpretation, an acoustic correlation framework was estab­lished. The log-derived acoustic impedance was blocked to optimize selection of boundaries. These were compared with wireline data, depositional model and seismic data to ensure lat­eral continuity. This approach enabled the accurate identification and positioning of first order reference horizons for inversion and reservoir model building. Furthermore, this inte­grated approach assisted in the identification of relevant units for assigning rock properties/reservoir characteristics. All of these elements are essential in building robust subsurface models.