AVA simultaneous inversion of partially stacked seismic amplitude data for the spatial delineation of lithology and fluid units of deepwater hydrocarbon reservoirs in the central Gulf of Mexico

Contreras, Arturo; Torres‐Verdín, Carlos; Fasnacht, Tim

doi:10.1190/1.2212276

Cited by 24 publications

(10 citation statements)

References 10 publications

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“…We recall that the l 1 -norm minimization method (sometimes it is referred as sparsespiky regularization in geophysics community) is quite important for seismic inversion (Claerbout and Muir 1973;Contreras et al 2006). This is because that the l 1 -norm could penalize outliers and large amplitude anomalies.…”

Section: Comparison With the Linear Programming Methodsmentioning

confidence: 99%

Hybrid regularization methods for seismic reflectivity inversion

2011

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In this paper, we consider new solution methods for seismic deconvolution problem in seismic data processing. We study regularization methods and introduce a hybrid regularization scheme for seismic deconvolution. Fast gradient descent methods are considered for solving the hybrid regularization model. An l 1 minimization model based on primal-dual interior point methods is presented and used for comparison. Numerical experiments for synthetic signal simulations and field data applications are given. The results show the potentials for applications of the developed method.

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Section: Comparison With the Linear Programming Methodsmentioning

confidence: 99%

Hybrid regularization methods for seismic reflectivity inversion

2011

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“…A numerical rock model is built to predict the elastic properties of the rock from the petrophysical properties [Sams 2007]. AVA deterministic simultaneous inversion is based on amplitude-versus-angle-constrained sparse spike inversion algorithm [Contreras 2006] which is an extension of the original constrained sparse spike inversion algorithm [Debeye 1990]. The inversion is a global, traced-based process that converts amplitudes from multiple partial angle stacks into P-impedance, Vp/Vs and Density volumes (elastic properties) which have higher resolution than the input seismic data.…”

Section: Methodsmentioning

confidence: 99%

Integrating Seismic and Well Data into Highly Detailed Reservoir Model through AVA Geostatistical Inversion

Sulistiono

Vaughan²,

Ali³

et al. 2015

Day 3 Wed, November 11, 2015

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Building a reservoir model by integrating seismic angle stacks and well data has been challenging for oil and gas companies. Seismic data contain very detailed information of reservoir properties lateraly but lack vertical resolution while well data provide very detailed information vertically but lack horizontal information. One established method of integrating these two kinds of data is deterministic seismic inversion. Deterministic seismic inversion has proven to be a good method in delineating the reservoirs at seismic resolution but it has limitation in analyzing thin reservoirs and it only pruduced one result. Geostatistical seismic inversion method has the ability to integrate many types of data and produce multiple relaizations of the results. The realizations are at much higher details than seismic data and are able to capture thin reservoirs.An AVA geostatistical seismic inversion workflow was successfully implemented to produce highly detailed reservoir models of Abu Madi reservoir sands in Nile delta, Egypt. Abu Madi Formation is composed of lacustrine turbidite deposits in semi-isolated basin and can be subdivided into Upper and Lower reservoirs. Intraformational shale baffles occur quite commonly within Abu Madi Formation which acted as barriers of pressure depletion between the Upper and Lower reservoirs. Well data analysis has demonstrated the complex pattern of the stacked reservoir sand zones of heterogeneous reservoir parameters and pressure trends. The main objective of the study was to produce reservoir models that could be used to understand the observed pressure depletion trends within the Upper and Lower Abu Madi reservoirs which have great significance for effective field management.Seismic angle stacks and well data were integrated through AVA geostatistical inversion to produce highly detailed lithotype and elastic property results at 0.5 ms vertical sampling. Thesse models have successfully captured the shale baffles. Lithotype and elastic property realizations were used to cosimulate for reservoir (engineering) properties of Effective Porosity and Volume of Clay. The Effective Porosity and Volume of Clay realizations were then ranked to provide the P10, P50 and P90 models to be used as input for dynamic flow simulation. Five permeability rock types were derived based on extensive SCAL database and used to define the permeability and saturation models. These detailed engineering models were used for dynamic flow simulation and successfully predicted the pressure depletion trends in the Abu Madi reservoirs.

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“…This technique which has been extended and widely publicised by Hedlin 2000, Hilterman 2001, Russell et al, 2003, and Contreras et al, 2006 has found wide application in industry, and has been employed in several successful theoretical and field studies in Niger Delta basin (see, for example Omudu et al, 2006Omudu et al, , 2008. Figure 2 shows crossplots of Ip versus Is and λρ versus µρ, colour coded with resistivity.…”

Section: Introductionmentioning

confidence: 96%

Seismic‐based lithology and fluid delineation of the ROK reservoir sand, shallow offshore Niger Delta

Nwogbo¹,

Omudu²,

Dike³

et al. 2009

SEG Technical Program Expanded Abstracts 2009

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Following the present global economic crises and the huge impact on energy prices, the industry is taking a pretty hard look at its development portfolio and is frantically searching for new and cheaper processes and workflows to help reduce costs, minimize risks and maintain a reasonable bottomline. Within the past few years quantitative seismic reservoir analysis has grown in popularity following a catalogue of successful results worldwide. With the robust tools and smart workflows at our disposal today, quantitative reservoir characterisation methods now represent a relatively cheap, fast and affordable technique for identifying and delineating hydrocarbon reservoirs in both carbonate and clastic regimes.We have implemented a rigorous simultaneous inversion workflow to analyse pre-stack seismic amplitude data and well logs from shallow offshore Niger Delta basin. Two partial angle stacks were simultaneously inverted to generate a 3D distribution of P-impedance, S-impedance, and density over the ROK reservoir interval. The pre-stack seismic inversion results and the modulus attributes derived from the main inversion products provided quantitative information about the geometry as well as the spatial distribution of highly-viable hydrocarbon bearing rocks across the field. The Monte Carlo and Bayesian analysis yielded predictions consistent with the results of the quantitative measurements.

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AVA simultaneous inversion of partially stacked seismic amplitude data for the spatial delineation of lithology and fluid units of deepwater hydrocarbon reservoirs in the central Gulf of Mexico

Cited by 24 publications

References 10 publications

Hybrid regularization methods for seismic reflectivity inversion

Hybrid regularization methods for seismic reflectivity inversion

Integrating Seismic and Well Data into Highly Detailed Reservoir Model through AVA Geostatistical Inversion

Seismic‐based lithology and fluid delineation of the ROK reservoir sand, shallow offshore Niger Delta

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