Seismic inversion and AVO analysis applied to predictive-modeling gas-condensate sands for exploration and early production in the Lower Magdalena Basin, Colombia

Luca, Mario Di; Salinas, Trino; Arminio, Juan F.; Alvarez, Gabriel; Álvarez, Pedro; Bolívar, Francisco; Marin, William

doi:10.1190/tle33070746.1

Cited by 4 publications

(3 citation statements)

References 5 publications

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“…Notice the good match between the seismic and well-log-derived S w . marine sequence, which was laid down in basin-floor conditions (Di Luca et al, 2014). Two wells (wells A and B) with a complete suite of high-quality measured elastic and petrophysical logs were available in the area (Figure 7), but only one of them (well A) was used in the analysis.…”

Section: Case Study 2: Onshore Colombiamentioning

confidence: 99%

Multiattribute rotation scheme: A tool for reservoir property prediction from seismic inversion attributes

Álvarez¹,

Bolívar²,

Luca³

et al. 2015

Interpretation

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The multiattribute rotation scheme (MARS) is a methodology that uses a numerical solution to estimate a transform to predict petrophysical properties from elastic attributes. This is achieved by estimating a new attribute in the direction of maximum change of a target property in an n-dimensional Euclidean space formed by an n number of attributes and subsequent scaling of this attribute to the target unit properties. We have computed the transform from well-log-derived elastic attributes and petrophysical properties, and we have posteriorly applied it to seismically derived elastic attributes. Such transforms can be used to estimate reservoir property volumes for reservoir characterization and delineation in exploration and production settings and to estimate secondary variables in geostatistical workflows for static model generation and reserve estimation. To illustrate the methodology, we applied MARS to estimate a transform to predict the water saturation and total porosity from elastic attributes in a well located in the Barents Sea as well as to estimate a water-saturation volume in a mud-rich turbidite gas reservoir located onshore Colombia.

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Section: Case Study 2: Onshore Colombiamentioning

confidence: 99%

Multiattribute rotation scheme: A tool for reservoir property prediction from seismic inversion attributes

Álvarez¹,

Bolívar²,

Luca³

et al. 2015

Interpretation

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“…Moreover, a geostatistical inversion method was used to predict reservoir properties in a higher certainty than that of deterministic methods [10]. In addition, some studies derived elastic properties from prestack seismic inversion to define facies [11,12]. Another straightforward methodology is to combine petroelastic modeling and stochastic inversion to predict hydrocarbon zones based on Bayesian theory [13].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Litho-Fluid Facies Distribution from Zero-Offset Acoustic and Shear Impedances

2022

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Seismic data are considered crucial sources of data that help identify the litho-fluid facies distributions in reservoir rocks. However, different facies mostly have similar responses to seismic attributes. In addition, seismic anisotropy negatively affects the facies predictors extracted from seismic data. Accordingly, this study aims at estimating zero-offset acoustic and shear impedances based on partial-stack inversion by two methods: statistical modeling and a multilayer feed-forward neural network (MLFN). The resulting impedance volumes are compared to those obtained from isotropic simultaneous inversion by using impedance logs. The best impedance volumes are applied to Thomsen’s anisotropy equations to solve for the anisotropy parameters Epsilon and Delta. Finally, the shear and acoustic impedances are transformed into elastic properties from which the facies and fluid distributions are predicted by using the logistic regression and decision tree algorithms. The results obtained from the MLFN show better matching with the impedance and facies logs compared to those obtained from isotropic inversion and statistical modeling.

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“…Seismic inversion data is commonly used in conjunction with reservoir static and dynamic modelling to help constrain reserve assessments, and has been effectively used both on the Julimar Brunello complex (Al-Duaij et al 2013) and on the Gorgon Field to the southwest (Van Der Weiden, Nayak, & Swinburn, 2012). In addition, there are several case studies in which inversion data has been used to de-risk exploration (Di Luca, et al, 2014), calculate net pay , or use stochastic inversion to assess sand connectivity in a simulation model (Moyen & Doyen, 2009). Previous work has shown that AVO inversion and lithology -prediction methods can assist in distinguishing gas from brine sands in this study area (Lamont, Thompson, & Bevilacqua, 2008).…”

Section: Introductionmentioning

confidence: 99%

Quantitative Interpretation: Use of Seismic Inversion Data to Directly Estimate Hydrocarbon Reserves and Resources

Shadlow¹,

Craig²,

Christiansen³

et al. 2018

ASEG Extended Abstracts

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SUMMARYA quantitative interpretation workflow utilising AVO inversion based lithology prediction data was developed to directly assess reserves and resources for an LNG development project in the Carnarvon Basin. The study area is covered by modern MAZ PSDM 3D seismic data using broadband acquisition and processing techniques, calibrated by numerous well intersections of the Triassic Mungaroo Formation reservoirs.Interpretation of the fluvio-deltaic reservoir bodies can be somewhat interpretive using 'traditional' workflows. By interpreting chronostratigraphic events tied to well-based biostratigraphy and then using the lithology prediction volumes, the interpretation of reservoir bodies becomes more objective.Seismic inversion data are typically used to qualitatively guide resource assessments, through amplitude mapping or use in static and dynamic modelling. In this case study, the inversion based prediction volumes are used to extract P90, P50 and P10 sand geobodies which are directly input into probabilistic reserve and resource assessments. The workflow is applied to discovered, developed, undeveloped and prospective reservoirs.Geobody extraction required the PSDM depth data to be accurately calibrated to wells. A calibrated velocity model was built by perturbing the imaging velocities in a 3D model to tie the chronostratigraphic events associated with all the reservoir intervals. Fluid contacts derived from wells were used to provide a depth cut-off to the geobody extractions.The resulting reserve and resource assessments from this workflow show an excellent match with previous assessments including static and dynamic modelling methods. The geobodies also identified previously unrecognised channel sands not easily interpreted on full and angle stack data.

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Seismic inversion and AVO analysis applied to predictive-modeling gas-condensate sands for exploration and early production in the Lower Magdalena Basin, Colombia

Cited by 4 publications

References 5 publications

Multiattribute rotation scheme: A tool for reservoir property prediction from seismic inversion attributes

Multiattribute rotation scheme: A tool for reservoir property prediction from seismic inversion attributes

Estimation of Litho-Fluid Facies Distribution from Zero-Offset Acoustic and Shear Impedances

Quantitative Interpretation: Use of Seismic Inversion Data to Directly Estimate Hydrocarbon Reserves and Resources

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