Mapping of carbonate mounds in the Brazilian presalt zone

Jesús, Carlos Echevarría; Azul, Maria Olho; Lupinacci, Wagner Moreira; Machado, Leandro

doi:10.1190/segam2017-17789870.1

Cited by 2 publications

(2 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After we analyzed the dominant frequency and identified the frequency bandwidth that best represents the target, we used HSD to decompose the seismic data into frequency bands. This frequency bandwidth is selected to calculate the envelope attribute from which a specific amplitude range is isolated (Jesus et al, 2017). We obtained the HSD parameters after SOF application to maintain the proportionality of the amplitude and thereby preserve the reservoir anomalies.…”

Section: Calculation Of Seismic Attributesmentioning

confidence: 99%

See 1 more Smart Citation

Multiattribute framework analysis for the identification of carbonate mounds in the Brazilian presalt zone

et al. 2019

Self Cite

View full text Add to dashboard Cite

Carbonate mounds, as described herein, often present seismic characteristics such as low amplitude and a high density of faults and fractures, which can easily be oversampled and blur other rock features in simple geobody extraction processes. We have developed a workflow for combining geometric attributes and hybrid spectral decomposition (HSD) to efficiently identify good-quality reservoirs in carbonate mounds within the complex environment of the Brazilian presalt zone. To better identify these reservoirs within the seismic volume of carbonate mounds, we divide our methodology into four stages: seismic data acquisition and processing overview, preconditioning of seismic data using structural-oriented filtering and imaging enhancement, calculation of seismic attributes, and classification of seismic facies. Although coherence and curvature attributes are often used to identify high-density fault and fracture zones, representing one of the most important features of carbonate mounds, HSD is necessary to discriminate low-amplitude carbonate mounds (good reservoir quality) from low-amplitude clay zones (nonreservoir). Finally, we use a multiattribute facies classification to generate a geologically significant outcome and to guide a final geobody extraction that is calibrated by well data and that can be used as a spatial indicator of the distribution of good reservoir quality for static modeling.

show abstract

Section: Calculation Of Seismic Attributesmentioning

confidence: 99%

“…Additionally, a frequency bandwidth related to seismic facies can be selected from a spectral decomposition analysis, so a specific amplitude range can be isolated that represents a reservoir anomaly (called HSD) (Jesus et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Multiattribute framework analysis for the identification of carbonate mounds in the Brazilian presalt zone

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

Geostatistics assisted by machine learning for reservoir property modeling: A case study in presalt carbonates of Buzios Field, Brazil

Ferreira

Oliveira²,

Castro

et al. 2021

The Leading Edge

View full text Add to dashboard Cite

An embedded model estimator (EMBER) petrophysical modeling algorithm has been applied to obtain effective porosity and permeability within the presalt carbonate reservoirs of the Barra Velha Formation in Buzios Field, Santos Basin. This advanced methodology was used due to the heterogeneity and complexity of the reservoirs, which makes modeling by conventional geostatistical methodologies difficult. For effective porosity modeling, we chose one facies model, one stratigraphic seismic attribute (acoustic impedance), and one structural seismic attribute (local flatness) as secondary variables. Permeability was modeled by using the best effective porosity simulation result as a secondary variable. Our results demonstrate that average effective porosity and permeability were 0.10 v/v and 440 md, respectively, indicating good reservoir quality throughout the studied area. A vertical trend of high effective porosities and permeabilities for the basal and uppermost reservoir sections was identified in our results, as well as a trend with lower values for these reservoir properties for the intermediate reservoir section. The lower section of the formation presented more continuity, and we infer it to be the best reservoir interval. We observed two horizontal trends for these reservoir properties at the formation top: one of higher values aligned to the north–south direction at the structural highs and another of lower reservoir properties related to isolated structural lows within structural highs. Correlation between modeled results and the blind test ANP-1 well upscaled properties was high, and upscaled well-log property distributions were preserved in the EMBER simulations, proving the predictive capacity of the algorithm. Finally, conditional distributions analysis indicated that the basal section of the Barra Velha Formation presents higher uncertainty for the estimation of effective porosity. Even though this interval is considered to have the best reservoir characteristics, decision making should be done with caution for this section.

show abstract

Mapping of carbonate mounds in the Brazilian presalt zone

Cited by 2 publications

References 15 publications

Multiattribute framework analysis for the identification of carbonate mounds in the Brazilian presalt zone

Multiattribute framework analysis for the identification of carbonate mounds in the Brazilian presalt zone

Geostatistics assisted by machine learning for reservoir property modeling: A case study in presalt carbonates of Buzios Field, Brazil

Contact Info

Product

Resources

About