Quantitative characterization of seismic thin beds: a methodological contribution using conventional amplitude and seismic inversion

Fervari, M.; Luoni, F.

doi:10.3997/1365-2397.2006023

Cited by 5 publications

(3 citation statements)

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“…Several approaches addressing the tuning effect in seismic reservoir characterization have been proposed and discussed by, among others, Brown et al (1984), Neff (1990aNeff ( , 1990b, Connolly (2007) and Simm (2009). In this case study, we describe the application of a technique proposed by Fervari and Luoni (2006) and already implemented in other similar settings and Amato et al, 2009). This method incorporates rock physics and forward seismic modeling for amplitude/isochron "de-tuned" calibration to Porosity*Thickness (PT) and Net Pay in the form of reservoir property deterministic maps for each considered seismic segment.…”

Section: Seismic Thin Bedsmentioning

confidence: 99%

Integrating The Geophysical Characterization Of Seismic Thin Beds With Stochastic Reservoir Modeling: A Case Study From The Kutei Basin (Offshore Kalimantan, Indonesia)

Cavanna

Caselgrandi

Corti³

et al. 2011

All Days

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TX 75083-3836, U.S.A., fax +1-972-952-9435 In exploration plays driven by DHI, seismic thin beds are common targets. When resolution capabilities are comparable to isochrones of remarkable elastic contrasts, reflections tend to fall around tuning thickness, where interference phenomena prevent a correct calibration of amplitudes to reservoir properties. If a de-tuning step is not applied in seismic characterization, wrong estimation of reservoir properties and pay thickness may lead to inaccurate volumetrics and misleading geologic models. These issues were faced in the characterization of a Kutei Basin (Offshore Kalimantan, Indonesia) discovery, where gas sands, acoustically marked by lower P-impedance than bounding shales, respond as bright, single-loop reflections (i.e. seismic thin beds). In order to support appraisal and reservoir modeling activities, our seismic characterization approach combined the following steps: a) Statistical tuning charts realization by extracting reservoir isochron and amplitude; b) Investigation of petro-elastic relations through rock physics modeling; c) Definition of deterministic tuning curves by generating a family of pseudo-reservoir responses via forward seismic modeling and d) De-tuned calibration of amplitude -isochron pairs to Porosity*Thickness (PT) and Net Pay. Appraisal wells confirmed the reliability of this approach but also revealed how other uncertainties may impact reservoir quality predictions. For this reason, PT realizations were only used as "soft" information in the reservoir model, built through a Sequential Indicator Simulation of sedimentological facies recognized in cores. Assuming a link between seismic porosity and facies, normalized porosity maps derived from PT estimates were used to condition the horizontal facies distributions and define a seismic-consistent variography. Sensitivity analysis confirmed the robustness of the approach and final results appear consistent with the de-tuned PT predictions. In a field where seismic thin beds affected by tuning represent the key geophysical issue to address, the applied workflow ensured the link between geophysics and geological modeling, from assessment of gas in-place to dynamic simulation.

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Section: Seismic Thin Bedsmentioning

confidence: 99%

Integrating The Geophysical Characterization Of Seismic Thin Beds With Stochastic Reservoir Modeling: A Case Study From The Kutei Basin (Offshore Kalimantan, Indonesia)

Cavanna

Caselgrandi

Corti³

et al. 2011

All Days

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“…He subsequently proposed a graphical transform technique in which extensive forward modelling results are used to establish a calibration template for prediction of reservoir parameters. Recently, Fervari and Luoni (2006) have also used this type of technique. The natural progression of these ideas is the use of forward modelling for inversion (e.g., Burge and Neff, 1998;Spikes et al, 2008).…”

Section: Net Pay From Band-limited Impedancementioning

confidence: 99%

Simple net pay estimation from seismic: a modelling study

Simm¹

2009

First Break

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Early modelling work on 'thin-bed' reservoirs (i.e., those below tuning thickness) comprising varying thicknesses of sand and shale was conducted, amongst others, by Meckel and Nath (1977) and Schramm et al. (1977). From simple reflection models they concluded that for thin zones the Abstract Amplitude scaling techniques are a simple way of removing the effect of tuning on seismic maps and predicting net pay thickness in low-impedance hydrocarbon-bearing sands. This modelling study addresses net pay prediction in layered sand/shale reservoirs using reflectivity and band-limited impedance approaches. It is demonstrated that net pay prediction using bandlimited impedance is more accurate than reflectivity. These techniques, however, are only appropriate in specific geological circumstances. Prior to application, it is advisable to evaluate potential accuracy through modelling as well as to consider the benefit of amplitude-versus-offset projections.www.firstbreak.org

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“…Net porosity thickness of the sand reservoir (or net pay) is then estimated by calibrating the tuning chart of the thickness model. In some cases, this technique was successful in estimating the clean sand thickness under tuning thickness [5,6].…”

Section: Introductionmentioning

confidence: 99%

Statistical Tuning Chart for Mapping Porosity Thickness: a Case Study of Channel Sand Bodies in the Kutei Basin Reservoir

2018

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Reservoir assessment is not only controlled by the structural framework but also stratigraphical features. Stratigraphical interpretation, which is related to seismic amplitude interpretation, is used to describe petrophysical aspects of channel sand reservoirs such as net porosity and thickness. This paper aims to map the porosity thickness for a case study of channel sand bodies reservoir in the Kutei basin. The study area is complex channel reservoir system that appears to occupy specific area within the depositional system. The geometry of the sediment channel, which thins toward the channel margins, makes this feature similar to be wedge model that could possibly be influenced by tuning effects. The tuning effects introduce pitfall in interpreting high-quality reservoir that is affected by contrasts in acoustic impedance. In order to distinguish high amplitude responses caused by tuning effects and acoustic properties, the analysis of amplitude responses needs to be correlated to the reservoir thickness. The statistical tuning chart is one of the techniques used to correlate amplitude responses and the reservoir thickness. The application of this technique to real data sets shows net porosity thickness map over the targeted reservoir. Thus, high-quality reservoir characterization can be performed to delineate geometric framework of the reservoir.

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Quantitative characterization of seismic thin beds: a methodological contribution using conventional amplitude and seismic inversion

Cited by 5 publications

References 0 publications

Integrating The Geophysical Characterization Of Seismic Thin Beds With Stochastic Reservoir Modeling: A Case Study From The Kutei Basin (Offshore Kalimantan, Indonesia)

Integrating The Geophysical Characterization Of Seismic Thin Beds With Stochastic Reservoir Modeling: A Case Study From The Kutei Basin (Offshore Kalimantan, Indonesia)

Simple net pay estimation from seismic: a modelling study

Statistical Tuning Chart for Mapping Porosity Thickness: a Case Study of Channel Sand Bodies in the Kutei Basin Reservoir

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