The effect of methodology on volumetric uncertainty estimation in static reservoir models

Beucher, Hélène; Renard, Didier; Doligez, Brigitte; Pontiggia, M.; Bellentani, Giuseppe

doi:10.1306/06040808069

Cited by 7 publications

(3 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These models optimized trace by trace by the ACO R -V and deconvolution filter can support a fast decision in improving estimation of reserves and making decisions regarding the development of the field [2], [24].…”

Section: Tests and Resultsmentioning

confidence: 99%

Fast Seismic Inversion Methods Using Ant Colony Optimization Algorithm

Conti

Roisenberg

Neto

et al. 2013

IEEE Geosci. Remote Sensing Lett.

View full text Add to dashboard Cite

This letter presents ACO R -V , a new computationally efficient ant-colony-optimization-based algorithm, tailored for continuous-domain problems. The ACO R -V algorithm is well suited for application in seismic inversion problems, owing to its intrinsic features, such as heuristics in generating the initial solution population and its facility to deal with multiobjective optimization problems. Here, we show how the ACO R -V algorithm can be applied in two methodologies to obtain 3-D impedance maps from poststack seismic amplitude data. The first methodology pertains to the traditional method of forward convolution of a reflectivity model with the estimated wavelet, where ACO R -V is used to guess the appropriate wavelet as the reflectivity model. In the second methodology, we propose an even faster inversion algorithm based on inverse filter optimization, where ACO R -V optimizes the inverse filter that is deconvolved with the seismic traces and results in a reflectivity model similar to that found in well logs. This modeled inverse filter is then deconvolved with the entire 3-D seismic volume. In experiments, both the methodologies are applied to a synthetic 3-D seismic volume. The results validate their feasibility and the suitability of ACO R -V as an optimization algorithm. The results also show that the second methodology has the advantages of a much higher convergence speed and effectiveness as a seismic inversion tool.

show abstract

Section: Tests and Resultsmentioning

confidence: 99%

Fast Seismic Inversion Methods Using Ant Colony Optimization Algorithm

Conti

Roisenberg

Neto

et al. 2013

IEEE Geosci. Remote Sensing Lett.

View full text Add to dashboard Cite

show abstract

“…Li et al applied multiple models to evaluate reservoir uncertainty [1]. Beucher et al divided the uncertainty of the reservoir into three levels: scale as well as shape of sand body, internal structure of sand body, and physical parameters [19]. Wu et al divided the uncertainty of the underground reservoir into random and fuzzy uncertainties [20].…”

Section: Introductionmentioning

confidence: 99%

Uncertainty Evaluation Method and Application of Reservoir Lithofacies Proportion under the Condition of Few Wells

Huang³

et al. 2022

Lithosphere

View full text Add to dashboard Cite

The proportion of different lithofacies is essential to determine the net-gross ratio, which directly affects the calculation of oil and gas reserves. Under the condition of few wells, the reliability of different lithofacies proportions obtained using well data is poor because it is difficult to estimate the uncertainty variation range of different lithofacies proportions. The present study overcomes this problem using an uncertainty evaluation method for reservoir lithofacies proportion. First, different lithofacies proportions of the reservoir are determined using the well and seismic data and are considered as the most likely estimated. Based on the lithofacies proportion, the lithofacies models of the study area are developed. Second, uniform and random methods are applied to sample the lithofacies models, and then, the probability distribution functions of different lithofacies proportions are derived. Third, the three levels of lithofacies proportions in the study area are calculated using the method of quantile and discretization of the probability distribution. Finally, we take M gas field as a sample and compare the test results of the fixed and random well structures. The results show that the sampling results of the fixed well structure model significantly deviate under the influence of the extension direction of the channel and well pattern distribution. Therefore, it is suggested to use random well structure to determine the uncertainty distribution range of lithofacies proportion.

show abstract

“…Tal como a simulação sequencial gaussiana, a simulação plurigaussiana é um método estocástico, possibilitando a criação de realizações equiprováveis e sua aplicação no cálculo de incertezas (Beucher et al, 2008).…”

Section: Simulação Plurigaussiana (Spg)unclassified

Modelagem geoestatística de fácies e porosidade para o Campo de Peregrino, Bacia de Campos-RJ, Brasil

Cunha¹

View full text Add to dashboard Cite

show abstract

The effect of methodology on volumetric uncertainty estimation in static reservoir models

Cited by 7 publications

References 8 publications

Fast Seismic Inversion Methods Using Ant Colony Optimization Algorithm

Fast Seismic Inversion Methods Using Ant Colony Optimization Algorithm

Uncertainty Evaluation Method and Application of Reservoir Lithofacies Proportion under the Condition of Few Wells

Modelagem geoestatística de fácies e porosidade para o Campo de Peregrino, Bacia de Campos-RJ, Brasil

Contact Info

Product

Resources

About