Heavy Oil Reservoir Characterization Using Vp/Vs Ratios from Multicomponent Data

Dumitrescu, Carmen C.; Lines, Larry

doi:10.3997/2214-4609.201401941

Cited by 5 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Dumitrescu and Lines (2007) compare this ratio derived by AVO analysis of conventional P-wave data and the ratio derived from multicomponent data. The seismic data are from a heavy-oil field (oil sands of the Devonian-Mississippian Bakken formation) near Plover Lake, Saskatchewan, Canada.…”

Section: Elastic Parameters From Avo Analysismentioning

confidence: 98%

1. Heavy-Oil Reservoirs: Their Characterization and Production

Chopra¹,

Lines²,

Schmitt³

et al. 2010

Heavy Oils

View full text Add to dashboard Cite

Section: Elastic Parameters From Avo Analysismentioning

confidence: 98%

1. Heavy-Oil Reservoirs: Their Characterization and Production

Chopra¹,

Lines²,

Schmitt³

et al. 2010

Heavy Oils

View full text Add to dashboard Cite

“…The V P /V S ratio or Poisson's ratio is essential for lithology identification and differs from wave velocities and impedances [52][53][54][55]. Since the cross plots of V P /V S vs. V P and V P /V S vs.…”

Section: Regularity In Cross Plotsmentioning

confidence: 99%

The Acoustic Characteristics of Tectonically Deformed Coal in Huaibei Coalfield

2023

View full text Add to dashboard Cite

Tectonically deformed coal (TDC) is closely related to gas outbursts. Since TDC exploration is an essential objective for coalfield exploration, it is of great significance to study the petrophysical properties of TDCs and explore their differences. This study collected 17 TDCs and undeformed coal samples from the Huaibei coalfield and ultrasonically tested their petrophysical parameters, including densities, P- and S-wave velocities, and their derived petrophysical parameters (VP/VS ratio, P- and S-wave impedances). Undeformed coal and TDCs with different deformation types (brittle, shear, and plastic deformations) show significant differences in their petrophysical parameters, and cross-plot analysis can directly differentiate them. As with traditional geological methods, acoustically measured petrophysical parameters are good indicators to determine the type of coal deformation. However, the TDCs with the same deformation type have similar petrophysical parameters; it is not easy to distinguish them directly. Instead, the proposed method incorporating principal component analysis and clustering can accurately distinguish up to five classes of TDCs. Different types of tectonic deformation environments and their intensities are highly correlated with the clustering results. This paper also provides essential petrophysical parameters for undeformed coal and TDCs in the Huaibei coalfield, and these parameters can help interpret undeformed coal and TDCs using wireline logs and seismic data.

show abstract

“…It is well known and accepted by the industry that inversion is a necessary step in imaging and interpreting the reservoir and there is a continuous struggle to improve the resolution of the inverted volume. Depending on the seismic data and the number of wells available, a Vp/Vs ratio volume can be obtained from: (i) traveltime measurements on the vertical and radial components of the multicomponent records (Lines et al, 2005), (ii) AVO analysis and simultaneous inversion using only the PP component (Dumitrescu et Lines, 2006), or (iii) joint inversion of the PP and PS (registered in PP time) poststack seismic data (Dumitrescu et Lines, 2007). In this project, prestack seismic data was processed through a model-based prestack inversion algorithm to produce P-impedance, S-impedance, Vp/Vs and density volumes.…”

Section: Introductionmentioning

confidence: 99%

Characterization of Heavy Oil Reservoir Using Vp/Vs Ratio and Neural Network Analysis

Dumitrescu¹,

Lines²,

Vanhooren³

et al. 2009

71st EAGE Conference and Exhibition Incorporating SPE EUROPEC 2009

Self Cite

View full text Add to dashboard Cite

The northeastern corner of Alberta contains an estimated 200 billion cubic metres of bitumen. Working interest partners Nexen Inc. and OPTI Canada Inc. hold rights to oil sands leases covering over 80,000 hectares in the Athabasca Oil Sands Region. The focus of this study is the southern portion of the Long Lake lease located approximately 40 km southeast of the City of Fort McMurray. The lease area is roughly 25,000 hectares and contains over 8 billion barrels of bitumen in place. It is well known, especially for heavy oil projects, that the Vp/Vs ratio is a good lithology discriminator. In this paper we provide Vp/Vs ratio volumes based on (i) deterministic prestack inversion and (ii) neural network analysis. From the prestack inversion the following volumes are estimated: P-impedance, Simpedance, density and Vp/Vs. The inversion approach accounts for the petrophysical relationship that exists in the logarithmic domain between: (1) P-impedance and S-impedance and (2) P-impedance and density. Neural network estimation of reservoir properties has proven effective in significantly improving accuracy and vertical resolution in the interpretation of the reservoir. Neural network analysis is performed on logs and pre-and post-stack seismic attributes. The Vp/Vs ratio volume from prestack inversion compared well with the similar volume obtained from neural network analysis. The latter results are sharper and offer more details in identification of the sand and shale within the heavy oil reservoir of Long Lake South.

show abstract

Heavy Oil Reservoir Characterization Using Vp/Vs Ratios from Multicomponent Data

Cited by 5 publications

References 0 publications

1. Heavy-Oil Reservoirs: Their Characterization and Production

1. Heavy-Oil Reservoirs: Their Characterization and Production

The Acoustic Characteristics of Tectonically Deformed Coal in Huaibei Coalfield

Characterization of Heavy Oil Reservoir Using Vp/Vs Ratio and Neural Network Analysis

Contact Info

Product

Resources

About