Seismic data provide essential information for guiding reservoir
development. Improvements in data quality hold the promise of improving
performance even further, provided that the value of these data exceeds their
cost. Previous work has demonstrated value-of-information (VOI) methods to
quantify the value of seismic data. In these examples, seismic accuracy was
obtained by means of expert assessment instead of being based on geophysical
quantities. In addition, the modeled seismic information was not representative
of any quantity that would be observed in a seismic image.
Here we apply a more general VOI model that includes multiple targets,
budgetary constraints, and quantitative models relating poststack seismic
amplitudes and amplitude-variation-with-offset (AVO) parameters to the
quantities of interest for reservoir characterization, such as porosity and
reservoir thickness. Also, by including estimated changes in data accuracy
based on signal-to-noise ratio, the decision model can provide objective
estimates of the reliability of measurements derived from the seismic data. We
demonstrate this methodology within the context of a west Texas 3D land survey.
This example demonstrates that seismic information can improve reservoir
economics and that improvements in seismic technology can create additional
Reservoir characterization makes heavy use of seismic data both for
selecting a target for drilling and, with time-lapse data, for monitoring the
fluid movements in the reservoir to optimize production of hydrocarbons.
Reservoir characterization requires good-quality seismic data for optimal
results. Improvements in aspects of seismic acquisition, such as
signal-to-noise ratio, bandwidth, receiver positioning, or maximum offset, may
help improve images or AVO analyses, thereby increasing the level of knowledge
about reservoir structure or properties.
However, modifications to acquisition procedures to estimate rock properties
better or to improve subsalt images, for example, may increase expense of data
acquisition and possibly experiment duration. The improved data quality must
always be weighed against the additional cost.
Previous work has addressed valuing seismic data using the decision-analysis
concept of VOI, including Stibolt and Lehman (1993), Waggoner (2000b, 2002),
Begg et al. (2002), Pickering and Bickel (2006), and Bickel et al. (2006).
Ballin et al. (2005) and Steagall et al. (2005) provide examples of actual
seismic projects where VOI analyses shaped management decisions significantly.
See Bratvold et al. (2007) for a review of VOI papers in the SPE
One challenge of implementing VOI methodologies to value seismic data is the
assessment of seismic accuracy. The studies discussed in the preceding
paragraph rely on expert assessment and model seismic information at a high
level. In many cases, these assessments are not tied directly to observable
seismic signals. For example, some studies assess the probability that the
seismic survey will report "success," "unswept," or "large
reservoir," even though the actual signal from a seismic survey may be an
amplitude reading. This gap between what seismic surveys actually report and
what is needed in decision making makes the implementation of VOI techniques
problematic (Bratvold et al. 2007). To address these concerns, several authors
have performed historical look-backs to document the impact of seismic
information [e.g. see Aylor (1999) and Waggoner (2000a)]. Another difficulty is
appropriately modeling the decision-making environment and the role seismic
information plays. Many authors implicitly embed downstream decisions in the
seismic-accuracy assessment by assuming the chance of geologic success can only
go up after commissioning a seismic survey (Head 1999; Waggoner 2000b, 2002).
This mixing of probability assessments and decision making makes it difficult
to understand the value of seismic in a specific situation.
Houck (2004) addressed some of these concerns by valuing seismic’s ability
to inform estimates of porosity in the context of a multiwell drilling program
and tying the accuracy of seismic data to directly observable seismic signals.
This paper also extends previous VOI studies by considering multiple targets
and budgetary constraints. We extend Houck’s results by investigating the
accuracy and value of AVO and peak amplitude. Furthermore, we examine the
ability of seismic information to inform estimates of multiple reservoir
properties simultaneously (e.g., porosity, thickness, and water saturation).
The resulting models allow quantification of the accuracy of information
provided by seismic data and quantification of the information’s economic
The contributions of this paper are three-fold. First, we illustrate a VOI
method that directly relates observable seismic signals to reservoir properties
and reservoir-management decisions. Second, we develop a seismic model that
allows us to quantify objectively the accuracy of seismic information across a
range of acquisition and processing techniques. Third, we quantify both the
absolute value of seismic information and the relative value of improved
seismic information within the context of a 3D land example situated in a
hypothetical carbonate reservoir modeled after the McElroy field in west
© 2008. Society of Petroleum Engineers
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- Original manuscript received:
28 June 2006
- Meeting paper published:
24 September 2006
- Revised manuscript received:
4 April 2008
- Manuscript approved:
23 April 2008
- Version of record:
25 October 2008