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Stress identification with an azimuthal inversion technique - a case study for a clastic oil field.

SEG workshop/forum/local conference, October, 2016
Ksenia Filippova | Irina Yakovleva | Yury Pavlovskiy | Peter Mesdag
©2016 SEG

Azimuthal inversion is state-of-the-art inversion technology for stress and fractured reservoir characterization and detection in anisotropic media. This technology requires a wide-azimuth seismic survey and careful azimuth dependent processing with noise attenuation. In this paper, the influence of noise attenuation on the reliability of anisotropic inversion results is discussed. The implementation of this technology for the understanding of horizontal stresses and the verification of the results with well data and microseismic will be presented.

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Optimizing the reservoir model of delta front sandstone using Seismic to Simulation workflow- A case study in the South China Sea

SEG - Society of Exploration Geophysicists, October, 2016
Lin Li | Bin Tao | HaiHong Wang | Shulin Sun | FengPing Mu | Wanlong Zhang | Jiapeng Ye
©2016 SEG

Offshore development requires detailed understanding of subsurface reservoirs and proper well placement. Use of all available information in an integrated reservoir model leads to improved production rates and higher EUR. Conventional methods use well logs, geologic information, and structure from seismic interpretation in static reservoir models, which, in turn, predict future production and evaluate alternative management scenarios. However, these models, which use different data types in isolation, often fail replicate past production (history matching). An integrated seismic-to-simulation workflow is presented in this paper; dense 3D seismic data provide a great deal of lateral lithofacies and rock-property information that is essential to the static model.

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3D VSP processing and imaging: A case study at Mad Dog, Gulf of Mexico

SEG - Society of Exploration Geophysicists, October, 2016
Chang-Chun Lee | Weiping Gou | Francis Rollins | Qingsong Li | Tianxia Jia | Samarjit Chakraborty
©2016 SEG

3D VSP data provides a unique opportunity to improve image resolution and fault definition in the vicinity of a well. However, the processing and imaging of VSP data requires special accommodations for its distinctive acquisition geometry. In this abstract, we demonstrate two key VSP pre-processing steps that greatly impacted the final image from the Mad Dog 3D VSP data, including XYZ vector field reorientation based on 3D elastic finite difference modelling, and shot-to-shot directional de-signature using near field hydrophone data. We also demonstrate how utilizing the multiple energy - in addition to primary - extends our capability to image the shallow overburden.

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Joint SRME and model-based water-layer demultiple for ocean bottom node

SEG - Society of Exploration Geophysicists, October, 2016
Hui Huang | Ping Wang | Jing Yang | Hui Chen | Pierre-Olivier Ariston | Imtiaz Ahmed | Nick Bassett
©2016 SEG

OBN SRME that combines OBN and streamer data is known to be an effective way to predict surface-related multiples in OBN data. However, the available streamer data often have limited offset/azimuth coverage. Additionally, the double source wavelets due to the cross-convolution of OBN and streamer data limit the bandwidth (loss of low and high frequency) of the multiple prediction. OBN model-based water-layer demultiple (MWD) overcomes such limitations and is a good complement of OBN SRME; MWD replaces the streamer data with the water-bottom Green’s function that has no offset/azimuth limitation and keeps the full bandwidth of the input data. With Gulf of Mexico (GOM) OBN data over the Atlantis field, we illustrate the benefit of joint SRME and MWD over solely SRME with the improved attenuation of low-frequency multiples and deep peg-leg multiples.

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Accounting for bias and uncertainty in facies estimations from deterministic inversions

SEG - Society of Exploration Geophysicists, October, 2016
John Pendrel | Henk Schouten | Raphael Bornard
©2016 SEG

Bayesian inference procedures can be used as interpretation tools for seismic inversions. The results are facies and their probabilities of occurrence derived from the native outcomes of inversions or their derivatives. Although deterministic inversions produce a single outcome, they have uncertainties associated with them. Further, due to inappropriate low frequency models or thin bedding, biases in the inversion properties can arise. We use a phenomenological approach to model these effects and separately correct for them in the subsequent Bayesian inference. The results are facies interpretations and pay maps which account for bias and uncertainties.

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