Acoustic impedance as a sequence stratigraphic tool in structurally complex deepwater settings

Contreras, Arturo; Latimer, Rebecca

doi:10.1190/1.3485768

Cited by 6 publications

(3 citation statements)

References 6 publications

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“…Sarkar et al (2010) suggest that sequential seismic geomorphologic analysis would produce sequential stratigraphic frameworks for more detailed prediction of sand-bodies. Contreras and Latimer (2010) adopted acoustic impedance as a sequential stratigraphic tool when analyzing depositional systems. Stratal slicing has received much attention (e.g., Zeng, 2010Zeng, , 2013.…”

Section: Introductionmentioning

confidence: 99%

Depositional model and evolution for a deep-water sublacustrine fan system from the syn-rift Lower Cretaceous Nantun Formation of the Tanan Depression (Tamtsag Basin, Mongolia)

Jia¹,

Liu²,

Miao³

et al. 2014

Marine and Petroleum Geology

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Section: Introductionmentioning

confidence: 99%

Depositional model and evolution for a deep-water sublacustrine fan system from the syn-rift Lower Cretaceous Nantun Formation of the Tanan Depression (Tamtsag Basin, Mongolia)

Jia¹,

Liu²,

Miao³

et al. 2014

Marine and Petroleum Geology

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“…Such is the fundamental gist of this paper with the added emphasis on strengthening interpretation of seismic inversions via attribute analysis (Barnes, 2001;Taner, 2001;Chopra and Marfurt, 2007), and long-standing qualitative and QI techniques described by various workers (Latimer et al, 2000;Chopra and Marfurt, 2008). In detail, this requires pairing selected interpretation aspects of deepwater settings as evidenced from seismic geomorphology and seismic stratigraphy (Weimer et al, 1998;Posamentier and Kolla, 2003;Contreras and Latimer, 2010) with statistical analyses (e.g., Latimer et al, 2000) and rock physics calibration (Avseth et al, 2005) under special consideration of geologic pitfalls and oddities, such as posed by the challenge of discriminating between volcanic sills and sand injectites in amplitude data (Werner, 2003;Jackson et al, 2011). Specifically, the intended scope of this paper has been to discuss selected aspects of qualitative and QI techniques that facilitate 1) quality control and calibration of inversion deliverables, 2) fast-track data reconnaissance, and 3) reservoir characterization, with special emphasis on successful prediction of fluid type(s) in deepwater settings.…”

Section: Discussionmentioning

confidence: 99%

From qualitative to quantitative interpretation: An interpreter’s guide to fluid prediction in Pliocene to Turonian deepwater turbidites from West Africa to Asia Pacific

Strecker¹,

Newton²,

Smith³

2014

Interpretation

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To mitigate exploration risk in deepwater settings, subsurface analysis increasingly has to rely on integration of qualitative with quantitative techniques. To predict pay in turbidite sandstones, proven statistical and analytical methods can routinely be run on well and seismic inversion data. However, quantitative interpretation (QI) should begin with a responsible audit of available well logs and seismic data, succeeded by data conditioning, proceeding with quality control, and placing elastic attribute responses within their geologic context. To address these issues, we evaluate geologic controls on porosity change as manifested by overpressure and compaction on calibration and analysis of elastic attributes. Following calibration of seismic inversion data, we provide tutorial-style interpretations of deepwater clastic reservoirs from the Gulf of Guinea, West Africa, to the Sabah trough, Borneo. Case study examples offer interpreters the potential to use workflows surrounding data mining in exploration or during field development. In our first example, a comparison of univariate statistics run on compressional-and shear-wave impedances and Poisson's ratio is introduced to potentially data mine 3D seismic over turbidite fairways. Joint interpretation of P-wave and S-wave impedances is combined with innovative uses of bivariate statistical analysis for anomaly detection. Additionally, the geologic rationale of interpreting elastic relationships of calibrated attributes, such as Lambda Rho and Mu Rho, is discussed on the seismic scale of a single reservoir layer using a combination of statistical methods and rock physics. Here, qualitative interpretation, via application of principles from seismic stratigraphy and seismic geomorphology, ultimately unlocks ambiguity in rock-physics-driven, quantitative lithology determination, guiding application of QI routines toward correctly predicting the prevailing fluid type. Elastic calibration permits seismic lithofacies classification of Cretaceous turbidite sandstones deposited as middle to lower slope channels canyon-fill and basin-floor channel complexes.

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“…Equation 10 becomes identical to equation 2 if the layer is horizontal. Such TTI model may represent channel-filled or turbidite sands embedded in shaly deposits, which are often found in continental slope areas (Contreras and Latimer, 2010;van Hoek et al, 2010). As is the case for VTI media, the moveout distortion in image gathers is primarily caused byk x2 , while errors ink x1 do not produce significant residual moveout (Figure 4).…”

Section: Tti Model With Quadratic Velocity Variationmentioning

confidence: 99%

Migration Velocity Analysis for TI Media in the Presence of Quadratic Lateral Velocity Variation

Takanashi

Tsvankin

2012

Proceedings

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One of the most serious problems in anisotropic velocity analysis is the trade-off between anisotropy and lateral heterogeneity, especially if velocity varies on a scale smaller than the maximum offset. We have developed a P-wave MVA (migration velocity analysis) algorithm for transversely isotropic (TI) models that include layers with small-scale lateral heterogeneity. Each layer is described by constant Thomsen parameters ε and δ and the symmetry-direction velocity V 0 that varies as a quadratic function of the distance along the layer boundaries. For tilted TI media (TTI), the symmetry axis is taken orthogonal to the reflectors. We analyzed the influence of lateral heterogeneity on image gathers obtained after prestack depth migration and found that quadratic lateral velocity variation in the overburden can significantly distort the moveout of the target reflection. Consequently, medium parameters beneath the heterogeneous layer(s) are estimated with substantial error, even when borehole information (e.g., check shots or sonic logs) is available. Because residual moveout in the image gathers is highly sensitive to lateral heterogeneity in the overburden, our algorithm simultaneously inverts for the interval parameters of all layers. Synthetic tests for models with a gently dipping overburden demonstrate that if the vertical profile of the symmetry-direction velocity V 0 is known at one location, the algorithm can reconstruct the other relevant parameters of TI models. The proposed approach helps increase the robustness of anisotropic velocity model-building and enhance image quality in the presence of small-scale lateral heterogeneity in the overburden.

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Acoustic impedance as a sequence stratigraphic tool in structurally complex deepwater settings

Cited by 6 publications

References 6 publications

Depositional model and evolution for a deep-water sublacustrine fan system from the syn-rift Lower Cretaceous Nantun Formation of the Tanan Depression (Tamtsag Basin, Mongolia)

Depositional model and evolution for a deep-water sublacustrine fan system from the syn-rift Lower Cretaceous Nantun Formation of the Tanan Depression (Tamtsag Basin, Mongolia)

From qualitative to quantitative interpretation: An interpreter’s guide to fluid prediction in Pliocene to Turonian deepwater turbidites from West Africa to Asia Pacific

Migration Velocity Analysis for TI Media in the Presence of Quadratic Lateral Velocity Variation

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