Structural uncertainty: a necessary step in geosciences risk analysis

Chavanne, Emmanuel; Brahmantio, Rangga A.; Douillard, A.; Irving, Alan

doi:10.1190/1.3064067

Cited by 7 publications

(1 citation statement)

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“…Accurate well placing in E&P requires accurate positioning of the interpreted geological structure in the depth domain. Technical risks related to the geological interpretation of the structure from seismic imaging are called structural risks and are critical to assess in both exploration and development (Chavanne et al 2008). These authors discussed propagation of seismic uncertainties into the geomodel.…”

Section: Structural Uncertainty Analysis For Exploration and Appraisalmentioning

confidence: 99%

Model‐uncertainty quantification in seismic tomography: method and applications

Osypov

Yang

Fournier

et al. 2013

Geophysical Prospecting

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Uncertainty is inherent in every stage of the oil and gas exploration and production (E&P) business and understanding uncertainty enables mitigation of E&P risks. Therefore, quantification of uncertainty is beneficial for decision making and uncertainty should be managed along with other aspects of business. For example, decisions on well positioning should take into account the structural uncertainty related to the non‐uniqueness of a velocity model used to create a seismic depth image. Moreover, recent advances in seismic acquisition technology, such as full‐azimuth, long‐offset techniques, combined with high‐accuracy migration algorithms such as reverse‐time migration, can greatly enhance images even in highly complex structural settings, provided that an Earth velocity model with sufficient resolution is available. Modern practices often use non‐seismic observation to better constrain velocity model building. However, even with additional information, there is still ambiguity in our velocity models caused by the inherent non‐uniqueness of the seismic experiment. Many different Earth velocity models exist that match the observed seismic (and well) data and this ambiguity grows rapidly away from well controls. The result is uncertainty in the seismic velocity model and the true positions of events in our images. Tracking these uncertainties can lead to significant improvement in the quantification of exploration risk (e.g., trap failure when well‐logging data are not representative), drilling risk (e.g., dry wells and abnormal pore pressure) and volumetric uncertainties. Whilst the underlying ambiguity can never be fully eradicated, a quantified measure of these uncertainties provides a valuable tool for understanding and evaluating the risks and for development of better risk‐mitigation plans and decision‐making strategies.

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Section: Structural Uncertainty Analysis For Exploration and Appraisalmentioning

confidence: 99%

Model‐uncertainty quantification in seismic tomography: method and applications

Osypov

Yang

Fournier

et al. 2013

Geophysical Prospecting

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From quantifying seismic uncertainty to assessing E&P risks and the value of information

Osypov¹,

Nichols²,

Woodward³

et al. 2011

SEG Technical Program Expanded Abstracts 2011

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Evaluating the Impact of Geophysical Uncertainties on Gross Rock Volume in a Low Relief Carbonate Field, offshore Abu Dhabi

Gazet¹,

Chavanne

Khalaf³

2009

All Days

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Quantifying the geophysical uncertainties is an important part of field evaluation because it has a direct impact on the extension of the oil pool and on the volumes in place. In low relief structures the uncertainty on Gross Rock Volume can be a major issue because small changes in the top reservoir depth map may drastically impact the closure area. Our field, offshore Abu Dhabi, is an example where this uncertainty issue on gross rock volume is important. The reservoir levels are located in the Lower Cretaceous Formation. A high standard OBC survey recently acquired drastically improved the vision of the field compared to previous sparse 2D lines of various vintages. This new 3D dataset also emphasized the importance of overburden events effects on the top reservoir time map. Signal phase instability appears to be affecting the dataset and hence the top reservoir time map. This paper presents the methodology followed to optimize the Gross Rock Volume estimation. Statistics as well as analytical methods are combined to assess carefully the uncertainties. The top reservoir time map is quality controlled with respect to key processing steps, overburden artifacts effects and picking uncertainty. The uncertainty related to time to depth conversion is assessed by scenarios around a selected base case. Multiple top reservoir map realizations are then computed, integrating all uncertainties. The objective of the study is to generate P10, P50 and P90 depth maps for the Top reservoir that fully integrate the whole range of geophysical uncertainties. These maps will then be implemented in the geological and reservoir models for further calculations to getP10, P50 and P90 reserves evaluation. Introduction Our field is a four way dip structure located offshore Abu Dhabi. Since discovery well, six vertical wells have been drilled to delineate the field extension and confirm development decision. As first phase field development is planned in the near future, a 3D OBC has been recently acquired. The aims of this 3D were to better define structural extension of the field, assess fault network in order to evaluate possible compartmentalization and eventually conduct reservoir characterization models for field development guidance. In this paper, we will deal with the structural definition of the field and will try to estimate the range of variation of its Gross Rock Volume (GRV). Compared to other regional structures, our field has a very low relief, estimated depth difference between the structural top and proved oil water contact is slightly over 100ft, which is very low compared to the average reservoir depth. With these conditions, uncertainty on top reservoir depth map may drastically change field extension and therefore associated volumetric assessments. This justified a study to identify and quantify uncertainties in an attempt to estimate the range of variation of the GRV and rank uncertainties contributors.

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Structural uncertainty: a necessary step in geosciences risk analysis

Cited by 7 publications

References 0 publications

Model‐uncertainty quantification in seismic tomography: method and applications

Model‐uncertainty quantification in seismic tomography: method and applications

From quantifying seismic uncertainty to assessing E&P risks and the value of information

Evaluating the Impact of Geophysical Uncertainties on Gross Rock Volume in a Low Relief Carbonate Field, offshore Abu Dhabi

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