Time-Lapse Seismic and Engineering Data Integration to Estimate Best Time for Seismic Acquisition Data

Ferreira, Carla Janaina; Schiozer, Denis José

doi:10.2118/164914-ms

Cited by 3 publications

(1 citation statement)

References 12 publications

(5 reference statements)

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“…To find the best time to acquire information, we use the methods by Ferreira et al (2011) and Ferreira and Schiozer (2013), which calculate an error function that represents the mismatch between the simulation scenario and the water saturation maps for the base model (Eq. (3)).…”

Section: Estimation Of the Acquisition Periodmentioning

confidence: 99%

Estimating the chance of success of information acquisition for the Norne benchmark case

Botechia

Santos

Barreto³

et al. 2018

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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A key decision in field management is whether or not to acquire information to either improve project economics or reduce uncertainties. A widely spread technique to quantify the gain of information acquisition is Value of Information (VoI). However, estimating the possible outcomes of future information without the data is a complex task. While traditional VoI estimates are based on a single average value, the Chance of Success (CoS) methodology works as a diagnostic tool, estimating a range of possible outcomes that vary because of reservoir uncertainties. The objective of this work is to estimate the CoS of a 4D seismic before having the data, applied to a complex real case (Norne field). The objective is to assist the decision of whether, or not, to acquire further data. The methodology comprises the following steps: uncertainty quantification, selection of Representative Models (RMs), estimation of the acquisition period, production strategy optimization and, finally, quantification of the CoS. The estimates use numerical reservoir simulation, economic analysis, and uncertainty evaluation. We performed analyses considering perfect and imperfect information. We aim to verify the increment in economic return when the 4D data identifies the closest-to-reality reservoir model. While the traditional expected VoI calculation provides only an average value, this methodology has the advantage of considering the increase in the economic return due to reservoir uncertainties, characterized by different RMs. Our results showed that decreased reliability of information affected the decision of which production strategy to select. In our case, information reliability less than 70% is insufficient to change the perception of the uncertain reservoir and consequently decisions. Furthermore, when the reliability reached around 50%, the information lost value, as the economic return became similar to that of the case without information acquisition.

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Section: Estimation Of the Acquisition Periodmentioning

confidence: 99%

Estimating the chance of success of information acquisition for the Norne benchmark case

Botechia

Santos

Barreto³

et al. 2018

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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Methodology To Estimate The Chance Of Success Of A Time-Lapse Seismic Project Using Reservoir Simulation

Ferreira

Schiozer

2014

All Days

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Time-lapse seismic technology has been successfully used in the petroleum industry. It provides important information regarding properties of the reservoir between and beyond the wells; 4D (time-lapse) seismic data is used as input for several processes, such as: well planning/completion; geological model constraining and reservoir simulation history matching. However, there are technical issues to be addressed before starting a 4D seismic project. Several geophysical studies use the chance of success concept to identify favorable cases; evaluating the seismic survey and the magnitude of seismic changes. However, from an engineering point of view it is important to evaluate the chances of business success, which relies on the use of the new information to identify infill well locations, increase the predictive capability of reservoir simulations, optimize the reservoir performance and develop well intervention programs. A 4D seismic project is considered an economic success if the impact on field operations generates more monetary benefit than the acquisition cost. The complex estimation should be based on field uncertainties and decision analysis. Given the importance and difficulty of predicting economic success, this paper presents a methodology to estimate the chance of success of a 4D seismic project from the engineering perspective applied to a synthetic model. The methodology was applied to a synthetic reservoir model to obtain a first estimate of the chance of success of a 4D seismic project for a specific production period. The process was performed in the developing phase and it comprises several methodologies such as: risk analysis, representative models selection, production strategy optimization and value of information concept. The presented methodology provides information of the chance of success of a 4D seismic project at a specific production period assisting the decision maker to evaluate the need for further analysis or to establish the acquisition or not of 4D seismic data. This decision is taken considering the acquisition cost, the increase of NPV due to new data and other influential factors. Thus, the main benefit derived from the acquisition of 4D seismic data was on the identification of remaining oil areas. Time-lapse seismic data has been successfully used in reservoir monitoring; several published cases report the success of its use in the improvement of production efficiency. But it is important to predict if acquiring new information will be profitable before the acquisition. This is a complex but essential part of time-lapse seismic reservoir management.

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A Probabilistic Approach to Quantify the Value of Information of 4D Seismic Projects

Ferreira

2015

Day 2 Tue, September 29, 2015

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A challenge that all managers face is to make decisions to maximize the project's return in the face of uncertainty. Acquisition of new information can assist decision makers in the reservoir management process. However, the acquisition of new information is not cost free and a routine business decision to be faced is whether acquiring new information is worthwhile. Consequently, the valuation of information becomes a significant part of a reservoir management process. The value of information (VOI) concept is commonly used to quantify the economic benefit resulted from the new information. The quantification of the VOI after the acquisition of information is simpler. In contrast, the VOI estimation before the acquisition of information is more complex because of the number of uncertainties and difficulties to model the problem; the term Expected Value of Information (EVOI) should be used in such context. The EVOI is based on average expectations; it is a weighted measure and does not show the variation of the expected benefits owing to reservoir uncertainties and consequently does not provide a complete picture of the problem. Thus, it is proposed a methodology that provides information about the possible range of outcomes increase and their probability. The methodology employs the chance of success (COS) concept, which provides more complete results. It applies the uncertainty analysis technique to generate multiple reservoir models, from which the fluid behavior establishes the period to acquire 4D seismic data. The representative models technique selects the models that represent the reservoir geological and economic variability. Finally, the impact of 4D seismic data on each representative model is quantified. The present study describes the methodology to estimate the COS, applies it to a synthetic model to validate the results and shows its benefits, as well as compares the EVOI and COS results obtained. The COS better supports the decision-making process due to its probabilistic approach. The decision maker can more meaningfully frame the range of potential increased returns and validate this against the organization's tolerance level. Such procedure makes the methodology an important tool for reservoir management.

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Time-Lapse Seismic and Engineering Data Integration to Estimate Best Time for Seismic Acquisition Data

Cited by 3 publications

References 12 publications

Estimating the chance of success of information acquisition for the Norne benchmark case

Estimating the chance of success of information acquisition for the Norne benchmark case

Methodology To Estimate The Chance Of Success Of A Time-Lapse Seismic Project Using Reservoir Simulation

A Probabilistic Approach to Quantify the Value of Information of 4D Seismic Projects

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