Quantifying 3D Land Seismic Reliability and Value

Abstract

Abstract Seismic data provide important information for guiding reservoir development. Improvements in data quality hold the promise of improving performance even further. Yet, the value of these data, and decision making capability, must exceed its cost. Previous work has demonstrated value of information (VOI) methods to quantify the value of seismic data. In these examples, seismic accuracy is obtained via expert assessment instead of being based on geophysical quantities. In addition, the modeled seismic information is not representative of a quantity that would be observed in a true processed seismic image. Here we apply a more general VOI model that includes multiple targets, budgetary constraints, and, importantly, quantitative models relating post-stack seismic amplitudes and AVO parameters to the quantities of interest for reservoir characterization, such as porosity and reservoir thickness. In addition, by including estimated changes in data accuracy related to signal-to-noise ratio, the decision model can provide objective estimates of the ability of the seismic data to provide reliable measurements and its value. We demonstrate this methodology within the context of a west Texas 3D land survey. This example demonstrates that seismic information can be quite valuable and improvements in seismic technology can create significant value for E&P companies. Introduction Reservoir characterization makes heavy use of seismic data for both 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 to provide improvements in images or amplitude variation with offset (AVO) analyses, thereby increasing the level of knowledge about reservoir structure or properties. However, improvements in acquisition design to resolve seismic imaging quality related to rock property definition or subsalt imaging, for example, may require increases in expenses related to data acquisition and, possibly, experiment duration. In a particular case, fundamental limitations in seismic image quality related to rock properties or to imaging challenges such as subsalt imaging may make the additional expense ineffective. In all cases, the improved data quality must be weighed against the additional cost. Previous work has addressed valuing seismic data using the decision analysis concept of value of information (VOI). For example, Stibolt and Lehman1, Waggoner2, 3, Begg et al.4, Pickering and Bickel5, and Bickel et al.6 illustrate the use of VOI techniques in valuing seismic information. Ballin et al.7 and Steagall et al.8 provide examples of actual seismic projects where VOI analyses played a significant role in shaping management decisions. One challenge of implementing VOI methodologies is the assessment of seismic accuracy. The studies discussed above rely on expert assessment and model seismic information at a high level. In many cases these assessments are not directly tied to observable seismic signals. For example, some studies assess the probability the seismic survey will report "success" or "unswept" or "large reservoir" when, in fact, 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 challenging and subject to criticism. To address these concerns, several authors have performed historical look-backs to document the impact of seismic information (see for example, Aylor9 and Waggoner10). Another difficulty is appropriately modeling the decision making environment and the role seismic information plays. For example, many authors implicitly embed downstream decisions in the seismic accuracy assessment by assuming the chance of success can only go up after commissioning a seismic survey.2, 3, 11 This mixing of probability assessments and decision making makes it difficult to understand the value of seismic in different situations.