Geologically Consistent History Matching of a Deepwater Turbidite Reservoir

Abstract

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThis paper presents an innovative methodology to integrate prior geologic information, well log data, seismic data and production data into a consistent 3D reservoir model. Furthermore, the method is applied to a real channel reservoir from the African coast. The methodology relies on the probability perturbation method. Perturbing probabilities rather than actual petrophysical properties guarantees that the conceptual geologic model is maintained and that any history matching related artifacts are avoided. Creating reservoir models that match all types of data are likely to have more prediction power than methods where some data are not honored. The first part of the paper reviews the details of the probability perturbation method (PPM), and the next part of this paper describes the additional work that is required to history match real reservoirs using this method. Then, a geological description of the reservoir case study is provided, and the procedure to build 3D reservoir models that are only conditioned to the static data is covered. Due to the character of the field, the channels are modeled with a multiple-point geostatistical method. The channel locations are perturbed in a manner such that the oil, water, and gas rates from the reservoir more accurately match the rates observed in the field. Two different geologic scenarios are used, and multiple history matched models are generated for each scenario. The reservoir has been producing for about five years, but the models are matched only to first three years of production. Afterwards, to check predictive power, the matched models are run for the last one and a half years, and the results compare favorably with the field data.

Quantifying geological uncertainty for flow and transport modeling in multi-modal heterogeneous formations

“…The mp-geostatistics concept was further elaborated by Strebelle [29,30] and has recently been applied successfully in numerous petroleum engineering applications (e.g., [17,19,26,27,32]). Strebelle [29] developed the single normal equation simulation (snesim) algorithm, an efficient non-iterative sequential simulation algorithm that obtains mp statistics from the training image(s) and anchors them to the actual subsurface data.…”

A Flow Based Reservoir Model Ranking Strategy

“…Probability Perturbation method (PPM) is developed to integrate production data without creating any artifacts in geological models 1,[5][6][7] . PPM treats production data as a probability cube which is a soft constraint for facies modeling and can be manipulated in a similar manner as seismic derived probability cube.…”

“…History match/ assisted history match (HM/AHM) are the champion of inversely integrating dynamic data for model updating 2,[4][5][6]9,13,15 . The original oil in place (OIP) is a good proxy for recoverable oil.…”

“…In this paper, a recently developed Probability Perturbation Method (PPM) is used in integrating production data by adjusting reservoir models honoring geological concepts 1,[5][6][7] . A practical reservoir modeling workflow should be able to mitigate uncertainties of reservoir parameters by integrating all available data instead of pushing for history match.…”

Adjoint-Based History Matching of Structural Models Using Production and Time-Lapse Seismic Data

“…Moreover, systematic criteria can be derived that help to determine which level of geologic model detail is flowrelevant or business-decision-relevant. Several authors have proposed such an integrated workflow, (Chierici, 1992;Caers, 2003;Hamman et al, 2003;Gross et al, 2004;Hoffman et al, 2005;Suzuki and Caers, 2006;Elrafie et al, 2009;Seiler et al, 2009;Kaleta et al, 2012). In this paper we do not employ a full Big Loop workflow, but, instead, we focus on updating some of the structural aspects of the static model.…”