Streamline-based assisted and automatic history matching techniques have shown great potential in reconciling high resolution geologic models to production data. Several field applications have demonstrated the efficiency of streamline-based sensitivity calculations together with the generalized travel time inversion (GTTI) for history matching. However, a limitation of the current GTTI based production data misfit calculations is that it is best suited for continuous and monotonic production histories. Field applications very often include active reservoir management decisions that involve well shut-in, recompletions and pattern conversions. These introduce significant discontinuities and non-monotonic effects in the production response.

In this paper we propose an efficient and novel technique that handles production discontinuities through a transformation of the production data and by eliminating high frequency details in the transformed domain. The technique also reduces nonmonotonic behavior and results in a response more suitable for the GTTI based misfit calculations. Our proposed approach has been applied to an offshore turbidite reservoir with active reservoir management and highly detailed production information. The static model contains more than three-hundred-thousand cells, complex sand depositional distribution combined with fault structures, four pairs of injector, deviated producing wells and more than 8 years of production history. Previous history matching attempts using traditional approaches had difficulties matching production response at the individual well level. With our proposed modification to the GTTI approach, a significant improvement on the well match quality was obtained. Most importantly, by visualizing the streamlines and the dynamic adjustment of flow paths during history matching, we could easily identify the areas of inconsistency between the geologic model and the production data. The calibrated geologic model suggests communication within sand channels, differences in flow paths and barriers that have not been included in the previous geologic and seismic interpretation.


Reconciling geological models with the production information is one of the most demanding tasks in reservoir characterization. The information contained in the dynamic data such as transient pressure, tracer or multiphase production histories can be used to identify high permeability channels and low permeability barriers in the geologic model. In addition, the dynamic information is fundamental to our understanding of the interaction between heterogeneity and fluid flow in the reservoir and the boundary conditions such as the interaction between the aquifer and the reservoir. It is well known that the geological features play a key role in decisions related to reservoir management and field development strategies (Landa et al., 1997). Traditionally the integration of production data has been performed by reservoir engineers by using local and regional multipliers of reservoir properties such as permeability and porosity. This procedure is highly subjective and requires a great deal of experience (Williams et al., 1998; Yang and Watson, 1988). More recently assisted or automatic history matching using inverse modeling has shown potential benefits related to preserving spatial continuity and geologic realism during history matching (Cheng et al., 2004; Reynolds et al., 1999; Landa et al., 1997; Brun et al., 2004). However, the solution of the inverse problem can be computationally expensive as it involves multiple solutions of the flow and transport equation to establish the relationship between the production response and the uncertain reservoir parameters (Datta-Gupta and King, 2007).

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