B. Todd Hoffman

Geologically Consistent History Matching of a Deepwater Turbidite Reservoir

This paper was selected for presentation by an SPE Program Committee following review of information contained in a proposal submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Papers presented at SPE meetings are subject to publication review by Editorial Committees of the Society of Petroleum Engineers. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to a proposal of not more than 300 words; illustrations may not be copied. The proposal must contain conspicuous acknowledgment of where and by whom the paper was presented. Abstract This 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 …

Geostatistical History Matching Using a Regional Probability Perturbation Method

This paper was selected for presentation by an SPE Program Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Papers presented at SPE meetings are subject to publication review by Editorial Committees of the Society of Petroleum Engineers. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of where and by whom the paper was presented. Abstract Petroleum reservoirs are large, geologically complex and usually contain multiple wells. Building numerical models for reservoirs is not a simple task, and it is further complicated when production data is incorporated into the reservoir models. Integrating production data into the model requires an iterative process of changing the model and observing how those changes effect the flow of fluids in the model. This process should be as efficient as possible because each iteration requires a time-consuming flow simulation, and it should honor all available data so that the predictive models are as accurate as possible. This paper lays out a general procedure for modifying geostatistical realizations in a geologically consistent manner that efficiently matches production data. To achieve this goal various regions in the reservoir are perturbed by different amounts, yet no geological artifacts are created at the borders of these regions. The methodology relies on a region-wise perturbation of the probability model used to generate the geostatistical realization. Perturbing probabilities rather than actual petrophysical properties guarantees that border artifacts are avoided. A new, simple yet efficient optimization method is developed that can jointly optimize the magnitude of the perturbations and is able to handle a large number of regions. We demonstrate with realistic synthetic examples that the method allows perturbing under various geological scenarios, and a 3D realistic synthetic case of a North Sea fluvial channel type reservoir demonstrates how the method would work in practice. Introduction Reservoir simulation has become a necessary tool of the petroleum engineer. It is …

History Matching Under Geological Control: Application to a North Sea Reservoir

Solutions to inverse problems are required in many Earth Science applications. The problem of determining reservoir properties, such as porosity and permeability from flow data, shortly termed “history matching”, is one example. In many traditional inverse approaches, certain model assumptions are made on either the data likelihood or the prior geological model, e.g. assumptions of conditional independence between data or Gaussianity on the distributions, which do not reflect the reality of actual data. This limits the applications of such approaches to practical problems like history matching. While modeling assumption are inevitable, this paper presents a general inversion technique that can be used with different geostatistical algorithms to create models that honor several types of prior geological information and at the same time match almost any type the data. The technique is built on the idea of perturbing the probability distributions used to create the models rather than perturb the properties directly. By perturbing the probabilities, the prior geological model as described by a geostatistical model or algorithm is maintained. We present a practical implementation of the probability perturbation method. A case study demonstrates how the practical implementation would work in an actual situation. The case study is a North Sea hydrocarbon reservoir where the production rates and pressure information are iteratively included in the model.