Improved resolution in Bayesian lithology/fluid inversion from prestack seismic data and well observations: Part 2 — Real case study

Geophysics ◽  
2010 ◽  
Vol 75 (2) ◽  
pp. B73-B82 ◽  
Author(s):  
Marit Ulvmoen ◽  
Henning Omre ◽  
Arild Buland
Keyword(s):  
Seismic Data ◽  
Cross Validation ◽  
Field Model ◽  
Gas Reservoir ◽  
Markov Random ◽  
Likelihood Model ◽  
Spatially Varying ◽  
Prior Models ◽  
Made In

We have performed lithology/fluid inversion based on prestack seismic data and well observations from a gas reservoir offshore Norway. The prior profile Markov random field model captures horizontal continuity and vertical sequencing of the lithology/fluid variables. The prior model is also locally adjusted for spatially varying lithology/fluid proportions. The likelihood model is inferred from basic seismic theory and observations in wells. An approximate posterior model is defined, which can be simulated from by an extremely computer-efficient algorithm. The lithology/fluid inversion results are compared to manual interpretations and evaluated by cross validation in one well. Moreover, inversions based on simplified prior models are developed for comparative reasons. Both lithology/fluid realizations and predictions look geologically reasonable. The results seem to reflect general reservoir experience and information provided by the prestack seismic data and well observations. The lithology/fluid proportions appear as geologically plausible and thin elongated lithology/fluid units are identified. The study is made in a 2D cross section, but extension to a full 3D setting is feasible.

Evaluation of direct hydrocarbon indicators through comparison of compressional‐ and shear‐wave seismic data: a case study of the Myrnam gas field, Alberta

Geophysics ◽  
1985 ◽  
Vol 50 (1) ◽  
pp. 37-48 ◽  
Author(s):  
Ross Alan Ensley
Keyword(s):  
Shear Wave ◽  
Seismic Data ◽  
Compressional Wave ◽  
Bright Spot ◽  
Low Velocity ◽  
Gas Reservoir ◽  
Gas Field ◽  
Compressional Waves ◽  
The Relationship

Shear waves differ from compressional waves in that their velocity is not significantly affected by changes in the fluid content of a rock. Because of this relationship, a gas‐related compressional‐wave “bright spot” or direct hydrocarbon indicator will have no comparable shear‐wave anomaly. In contrast, a lithology‐related compressional‐wave anomaly will have a corresponding shear‐wave anomaly. Thus, it is possible to use shear‐wave seismic data to evaluate compressional‐wave direct hydrocarbon indicators. This case study presents data from Myrnam, Alberta which exhibit the relationship between compressional‐ and shear‐wave seismic data over a gas reservoir and a low‐velocity coal.

scholarly journals Lithofacies classification using Bayes theorem method : Case study Western Desert, Egypt

2021 ◽  
Vol 11 (1) ◽  
pp. 76-89
Author(s):  
Abdelrahman Moataz Mohamed Gomaa
Keyword(s):  
Bayesian Method ◽  
Cross Validation ◽  
Bayesian Classification ◽  
Western Desert ◽  
Classification Method ◽  
Gas Reservoir ◽  
L2 Norm ◽  
Tight Reservoirs ◽  
Lithofacies Classification

This paper shows the availability of using the Bayesian classification method to predict class membership probabilities in one of the deep tight reservoirs in Western Desert, Egypt. The workflow of our project that using the Bayesian method used the deterministic petrophysical results of three training wells to train the data and extract the classifiers. The classified data were modeled using Gaussian distribution for each lithofacies. The used wells were acquired from a deep Jurassic gas reservoir in the Western Desert of Egypt. The fitting between actual and modeled data has been reached by minimizing the L2 norm. Besides, a cross-validation process was used for validating the resulted classifiers. Finally, the Bayesian classification method can predict the GWC with an accuracy of 4 m. To avoid probability interference caused by the compacted shale more data should be added to the initial model.

Impact of rock-physics depth trends and Markov random fields on hierarchical Bayesian lithology/fluid prediction

Geophysics ◽  
2010 ◽  
Vol 75 (4) ◽  
pp. R93-R108 ◽  
Author(s):  
Kjartan Rimstad ◽  
Henning Omre
Keyword(s):  
Parameter Uncertainty ◽  
Seismic Data ◽  
Markov Random Fields ◽  
Petroleum Reservoirs ◽  
Rock Physics ◽  
Real Data ◽  
Model Parameter ◽  
Markov Random ◽  
Likelihood Model ◽  
Model Parameter Uncertainty

Early assessments of petroleum reservoirs are usually based on seismic data and observations in a small number of wells. Decision-making concerning the reservoir will be improved if these data can be integrated and converted into a lithology/fluid map of the reservoir. We analyze lithology/fluid prediction in a Bayesian setting, based on prestack seismic data and well observations. The likelihood model contains a convolved linearized Zoeppritz relation and rock-physics models with depth trends caused by compaction and cementation. Well observations are assumed to be exact. The likelihood model contains several global parameters such as depth trend, wavelets, and error parameters; the inference of these is an integral part of the study. The prior model is based on a profile Markov random field parameterized to capture different continuity directions for lithologies and fluids. The posterior model captures prediction and model-parameter uncertainty and is assessed by Markov-chain Monte Carlo simulation-based inference. The inversion model is evaluated on a synthetic and a real data case. It is concluded that geologically plausible lithology/fluid predictions can be made. Rock physics depth trends have influence when cementation is present and/or predictions at depth outside the well range are made. Inclusion of model-parameter uncertainty makes the prediction uncertainties more realistic.

Dissolution Facies Window Identification of Carbonate Gas Reservoir by Using Electrical Image Logs: A Case Study from Sichuan Basin

2021 ◽  
Author(s):  
Bing Xie ◽  
Qiang Lai ◽  
Jing Mo ◽  
Li Bai ◽  
Wenjun Luo ◽  
...  
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Gas Production ◽  
Gas Reservoir ◽  
Real Gas ◽  
Facies Model ◽  
Dolomite Formation ◽  
Secondary Pore

Abstract Predicted reservoir results from conventional methods didn’t match the production performance in GS B well block in the Lower Sinian Dengying dolomite formation. The predicted gas production of vertical well is around 500k m3/day, but the real gas production is below 100k m3/day. In GS A well block, the predicted gas production of vertical well is consistent with the real gas production around 500k m3/day, and when meter cavie develops, test gas production can reach 1000k m3/day. It suggests the biggest challenge is to clarify reservoir characterization in GS B well block. However, due to the limited resolution of conventional logs and strong heterogeneity of carbonate reservoir, conventional open hole logs and seismic data has limitation to provide the details of secondary pore and fractures to clarify reservoir characterization. The electrical image logs provide high resolution images with high borehole coverage. It can provide abundant information about secondary pore and fracture to identify dominant dissolution facies window. Through electrical image logs, secondary pore and fracture classification in 50 vertical wells were performed in the Lower Sinian Dengying dolomite formation. Five facies were detected based on electrical image logs, including vug facies (honeycomb vug facies, algal stromatolite vug facies and bedding vug facies), cave facies, fracture-vug facies, massive dense facies and dark thin layer dense facies. With the five facies and top interface constraints from seismic data, 3D dissolution facies model was created, which can show different dissolution facies window of GS A and GS B well block. The method in this paper reveals the reason of confliction and agree test gas production. The case study presents how to identify five dissolution facies based on high-resolution electrical image logs with core data calibration. Besides, 3D dissolution facies model is created to show dissolution facies window of GS B well block to optimize well trajectory deployment during the development stage. Better understanding of reservoir characterization was instructive for acid fracturing design of Dengying dolomite gas reservoir as well.

PROCESSING AND IMAGING OF MARINE SEISMIC DATA FROM THE JEQUITINHONHA BASIN (BAHIA, BRAZIL)

2016 ◽  
Vol 33 (3) ◽  
Author(s):  
Lourenildo W.B. Leite ◽  
J. Mann ◽  
Wildney W.S. Vieira
Keyword(s):  
Seismic Data ◽  
Sedimentary Basins ◽  
Study Results ◽  
Marine Seismic ◽  
Present Case Study

ABSTRACT. The present case study results from a consistent processing and imaging of marine seismic data from a set collected over sedimentary basins of the East Brazilian Atlantic. Our general aim is... RESUMO. O presente artigo resulta de um processamento e imageamento consistentes de dados sísmicos marinhos de levantamento realizado em bacias sedimentares do Atlântico do Nordeste...

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