This study presents a new method to improve production forecasts and reserves estimation for a multilayer well in the early stages of production, using Arps’ hyperbolic decline method to model the decline rate of each layer. The method can be applied to both oil and gas wells.

The new approach generates the profiles of instantaneous decline rate (D) and instantaneous decline exponent (b) from the historical flow rate (q). Because of the inherent noise in the production data, a regression technique is applied to smooth the flow rate data and the analysis is performed on the smoothed data. History matching is performed not only on the profile of q, but also on the profiles of D and b. The results are the unique decline parameters (qi, Di, and b) for each layer.

For a multi-layer well, the values of D and b vary with time, which means that its performance cannot be modeled using a conventional single-layer well approach. Furthermore, the well-known non-uniqueness problem from history matching is magnified in a multilayer well: many models can successfully match the production profile in the short term but fail to match it in the longer term. Only the correct model can match the profiles of q, D, and b over both the short-term and the long-term. The proposed method provides the correct unique decline parameters (qi, Di, and b) for each layer, during the early stage of production, and these parameters are then valid for the life of the well. The method works well for both synthetic examples and actual field data.

The novelty of the new methodology is the ability to provide the decline parameters for each layer at an early stage of production, which can then be used for production forecasting in the long term. The non-uniqueness problem from history matching is solved.

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