What seismic velocity field for pore pressure prediction?

Cibin, Patrizia; Martera, M. Della; Buia, Michele; Calcagni, D.; Runcer, D. Joe; Talkan, Tarek

doi:10.1190/1.1851132

Cited by 5 publications

(5 citation statements)

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“…The choice of the attribute to use depends on many factors, as the complexity of the area under study in terms both of structure and pressure regime, data and time available to perform the study and of course the costs required to carry out it. (Cibin P. et al 2004) With Continuous Velocity Analysis (CVA) technique a very dense and detailed velocity field can be generated starting from the PSTM velocities elaborated during the time processing. Each gather is stacked after NMO correction with many trial functions and the stacked traces are scanned to find the highest amplitude at every time sample.…”

Section: Discussionmentioning

confidence: 99%

“…The Grid Tomography is based on ray tracing techniques to compute the residual moveouts and takes information not only from geological consistent reflecting horizons, but also from local events, seismically coherent, interpretable just in restricted areas of the model. Also in this case, the possibility to depart from a definite horizons based model using further information from extra seismic events, gives the opportunity to highlight velocity anomalies in the updated velocity field often associated to pore pressure anomalies (Cibin P.2006, 2008, 2010and Colin Sayers, 2000.…”

Section: Discussionmentioning

confidence: 99%

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Pore Pressure Prediction in HP/HT environment

Cibin

Martera

Andreoletti

et al. 2010

ASEG Extended Abstracts

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Pore Pressure Prediction in HP/HT environment

Cibin

Martera

Andreoletti

et al. 2010

ASEG Extended Abstracts

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“…Both velocities can be used quite successfully where the theoretical conditions for the application of Dix equation are valid. With Continuous Velocity Analysis (CVA) techniques, the PSTM velocities are used as initial reference functions in a refining process giving a very dense and detailed velocity field as output and generating a pore pressure field that can highlight over pressure anomalies in not too much complex areas [Cibin P., (2004)]. …”

Section: Methodsmentioning

confidence: 99%

“…Once all the terms of Eaton formula are defined, the seismic interval velocities cube can be converted into effective stress cube. At the end of the process, the pore pressure volume is obtained by subtracting the effective stress volume to the overburden volume and then the overpressure volume is calculated as difference between the pore pressure volume and the hydrostatic pressure volume [Cibin P., (2008)]. …”

Section: Methodsmentioning

confidence: 99%

Enhanced Seismic Velocity Processing to Improve 3D Geopressure Evaluation

Cibin

Martera

Andreoletti

et al. 2010

SPE Annual Technical Conference and Exhibition

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Geopressure evaluations are key considerations for successful well planning and drilling. The necessity to satisfy the world needs of oil & gas presses Oil Companies to drill in conditions that are getting harder and harder in terms of geopressure environment. The pore pressure prediction accuracy has a large impact on the cost of a project and is especially critical for drilling hightemperature/high-pressure (HP/HT) wells where there is a small margin between pore and fracture pressures. This paper outlines the most accurate methodologies to estimate seismic velocities to be used for the pore pressure prediction. In exploration, pore pressure prediction is critical for the evaluation of vertical and lateral sealing, the estimation of maximum possible column of hydrocarbons in place, and consequently to rank the prospects and evaluate the economics. As far as concerns drilling, the geopressure information is important to define the best well design in order to reduce costs, NPT (Not Productive Time), wellbore stability, sand production and reservoir damages. Generally, in complex and deep areas, conventional velocity fields derived from seismic time processing are often not accurate enough to make a correct pore pressure prediction. For this reason, several methods have been developed trying to obtain more appropriate velocity fields. In this paper we compare some of them, mainly CVA (Continuous Velocity Analysis) calculated in the time domain versus Grid Tomography, applied in the depth domain. In particular, Eni proprietary software based on reflection tomography, able to integrate geological information in the Grid Tomography loop, has been successfully applied in North Africa, where the exploration goal is to reach deep HP/HT targets. Besides, in that region, strong pressure anomalies and pressure compartments are frequently present in the shallower layers, due to compaction disequilibrium and vertical pressure transfer along faults or through windows in salt layer. These phenomena have created serious problems during drilling operations in the past and a good geopressure prediction can considerably reduce drilling costs and risks. The application of the proposed methodology to build the seismic velocity field has been important both in defining more detailed pore/over pressure volumes and structural models by an iterative pre stack depth migration workflow.

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“…As part of the seismic processing work-flow, several velocity models can be derived ranging from simple normal-moveout to tomographic inversion and more recently to full-wave inversion. The choice of which to use depends on the complexity of the problem (Cibin et al, 2004).…”

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confidence: 99%

A sequential dynamic Bayesian network for pore-pressure estimation with uncertainty quantification

et al. 2018

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Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Abstract Pore-pressure estimation is an important part of oil-well drilling, since drilling into unexpected highly pressured fluids can be costly and dangerous. However, standard estimation methods rarely account for the many sources of uncertainty, or for the multivariate nature of the system. We propose the pore pressure sequential dynamic Bayesian network (PP SDBN) as an appropriate solution to both these issues. The PP SDBN models the relationships between quantities in the pore pressure system, such as pressures, porosity, lithology and wireline log data, using conditional probability distributions based on geophysical relationships to capture our uncertainty about these variables and the relationships between them. When wireline log data is given to the PP SDBN, the probability distributions are updated, providing an estimate of 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 This paper presented here as accepted for publication in Geophysics prior to copyediting and composition. © 2018 Society of Exploration Geophysicists. Page 1 of 47 GEOPHYSICS

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What seismic velocity field for pore pressure prediction?

Cited by 5 publications

References 1 publication

Pore Pressure Prediction in HP/HT environment

Pore Pressure Prediction in HP/HT environment

Enhanced Seismic Velocity Processing to Improve 3D Geopressure Evaluation

A sequential dynamic Bayesian network for pore-pressure estimation with uncertainty quantification

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