Richard T. Houck

Quantifying the uncertainty in an AVO interpretation

Lithologic interpretations of amplitude variation with offset (AVO) information are ambiguous both because different lithologies occupy overlapping ranges of elastic properties, and because angle-dependent reflection coefficients estimated from seismic data are uncertain. This paper presents a method for quantifying and combining these two components of uncertainty to get a full characterization of the uncertainty associated with an AVO-based lithologic interpretation. The result of this approach is a compilation of all the lithologies that are consistent with the observed AVO behavior, along with a probability of occurrence for each lithology. A 2-D line from the North Sea illustrates how the method might be applied in practice. For any data set, the interaction between the geologic and measurement components of uncertainty may significantly affect the overall uncertainty in a lithologic interpretation.

Time-lapse seismic repeatability- : How much is enough?

Acquisition and processing of time-lapse seismic surveys are usually directed toward maximizing the repeatability of the final image. Given the amount of effort devoted to realizing this goal, it is reasonable to ask if we ever reach the point where we have all the repeatability we need. More precisely, does repeatability ever become sufficiently good that further improvement is not worth the additional effort? This article addresses this question using model-based value of information analysis (VOI).

Predicting the economic impact of acquisition artifacts and noise

Decisions that involve trade-offs between data quality and cost arise frequently in seismic acquisition. Improvements in data quality are always desirable, but they usually involve increased cost. To justify spending more money to acquire higher quality data, we need to show that the higher data quality has economic benefits that offset any increased expense. This article shows how we can use value of information (VOI) analysis and probabilistic modeling to quantify the economic value of seismic data, and to predict the economic consequences of changes in data quality.

Evaluating reconnaissance CSEM survey designs using detection theory

Marine controlled-source electromagnetic (CSEM) surveys have recently found wide application for mapping resistive hydrocarbon reservoirs (Ellingsrud et al., 2002). Typically, these surveys have been target oriented and have been used to delineate potential reservoirs already mapped by other methods. However, CSEM surveys can also be used for reconnaissance in areas where no specific targets have been identified (Srnka et al., 2005). The objective of a reconnaissance CSEM survey is to detect the presence of resistive bodies that are large enough to be economic hydrocarbon reservoirs. These bodies would then be candidates for more detailed seismic or CSEM surveys.

Simulation of Multi-azimuth Data Acquisition And 4D Seismic Imaging Repeatability

A major objective of 4D acquisition and processing is to maximize data repeatability. Ideally, all differences between the processed images for the base and monitor surveys should be associated with changes in reservoir conditions. In practice, however, differences in base and monitor acquisition geometry, noise, and overburden properties can also produce differences in the processed images. In this study, we simulated multi-azimuth 4D acquisition and quantified the contributions of these factors to non-production related differences in reservoir imaging. The simulation integrates both ray-tracing modeling and migration so that synthetic repeatability can be directly compared with field data-derived repeatability. The results of this work will aid in developing methods that can be used to mitigate non-repeatability for future 4D seismic.