Rocky Roden

Geologic pattern recognition from seismic attributes: Principal component analysis and self-organizing maps

Interpretation of seismic reflection data routinely involves powerful multiple-central-processing-unit computers, advanced visualization techniques, and generation of numerous seismic data types and attributes. Even with these technologies at the disposal of interpreters, there are additional techniques to derive even more useful information from our data. Over the last few years, there have been efforts to distill numerous seismic attributes into volumes that are easily evaluated for their geologic significance and improved seismic interpretation. Seismic attributes are any measurable property of seismic data. Commonly used categories of seismic attributes include instantaneous, geometric, amplitude accentuating, amplitude-variation with offset, spectral decomposition, and inversion. Principal component analysis (PCA), a linear quantitative technique, has proven to be an excellent approach for use in understanding which seismic attributes or combination of seismic attributes has interpretive significance. The PCA reduces a large set of seismic attributes to indicate variations in the data, which often relate to geologic features of interest. PCA, as a tool used in an interpretation workflow, can help to determine meaningful seismic attributes. In turn, these attributes are input to self-organizing-map (SOM) training. The SOM, a form of unsupervised neural networks, has proven to take many of these seismic attributes and produce meaningful and easily interpretable results. SOM analysis reveals the natural clustering and patterns in data and has been beneficial in defining stratigraphy, seismic facies, direct hydrocarbon indicator features, and aspects of shale plays, such as fault/fracture trends and sweet spots. With modern visualization capabilities and the application of 2D color maps, SOM routinely identifies meaningful geologic patterns. Recent work using SOM and PCA has revealed geologic features that were not previously identified or easily interpreted from the seismic data. The ultimate goal in this multiattribute analysis is to enable the geoscientist to produce a more accurate interpretation and reduce exploration and development risk.

The impact of seismic amplitudes on prospect risk analysis

Essentially all companies involved in oil and gas exploration and development must account for the various geologic risk factors associated with their specific prospects. Since seismic data (calibrated with well control if available) are a primary interpretation tool to determine these risk factors, the presence of seismic amplitudes that are potentially associated with oil or gas pays is extremely important. However, interpreters evaluating prospects have had to inherently know how seismic amplitudes impact the geologic chance factors and ultimately the probability of drilling success (Pg).

The significance of phase to the interpreter: Practical guidelines for phase analysis

Whether making a quick interpretation from paper sections in a data room or controlling every aspect of seismic acquisition/processing/interpretation over a company’s property, the interpreter is responsible for the final results. The interpreter must make decisions on the quality and the limitations of the seismic data so final interpretations are valid. The phase of the data is one of the critical seismic attributes in which interpreters have to assume additional responsibility. An explorationist will tend to look at the data phase attribute as part of a more regional approach. Reservoir geophysicists will focus on a particular zone of interest associated with specific reservoirs. Regardless, a fundamental understanding of the phase of seismic data is critical for the interpretation of stratigraphic variations, calibration of well control, modeling of geologic features, evaluation of acoustic responses (impedance inversion), and accurate quantification of oil and gas reserves.

The Role of AVO in Prospect Risk Assessment

AbstractEssentially all companies exploring for oil and gas should perform a risk analysis to understand the uncertainties in their interpretations and to properly value order prospects in a company’s drilling portfolio. For conventional exploration in clastic environments, primarily sands encased in shales, a key component of the risk analysis process is evaluating direct hydrocarbon indicators, which can have a significant impact on the final risk value. We investigate the role AVO plays in the risk assessment process as a portion of a comprehensive and systematic DHI evaluation. Documentation of the geologic context and quantification of data quality and DHI characteristics, including AVO characteristics, is necessary to properly assess a prospect’s risk. A DHI consortium database of over 230 drilled prospects provides statistics to determine the importance of data quality elements, primarily in class 2 and 3 geologic settings. The most important AVO interpretation characteristics are also identified b...

Risking seismic amplitude anomaly prospects based on database trends

Many oil companies routinely evaluate prospects for their drilling portfolio and seismic amplitude anomalies play an important role in this process. When these anomalies occur at a potential reservoir level, they are often called DHIs or direct hydrocarbon indicators, which are changes in reflection response that may be related to oil and/or gas accumulations. Examples of DHIs include bright spots, flat spots, dim spots, character/phase change at a projected oil or gas/water contact, and an amplitude variation with offset. Many uncertainties should be considered and analyzed in the process of assigning a probability of success and resource estimate range before including a seismic amplitude anomaly prospect in an oil companys prospect portfolio.

The impact of prestack data phase on the AVO interpretation workflow—A case study

In the conventional approach of interpreting stacked seismic data, it is quite common to rotate the phase of the data to match synthetic correlations and/or to get isolated reflections in the data as close as possible to zero phase. Understanding the phase of the data is extremely important in the interpretation workflow and has significant implications for the final interpretation and drilling of wells. This functionality is available on most interpretation systems today. What is not routine in the normal interpretation process is to phase rotate gathers to determine how this affects the final stacked volume, the analysis of the prestack data, and ultimately the final interpretation of the prospect.

The evolution of the interpreter's toolkit—past, present, and future

Geophysical interpreters today take for granted the availability and access to computer workstation environments loaded with 2D/3D seismic surveys, well logs, geological studies, and GIS information. To appreciate what interpreters have at their disposal today, I have made an attempt to review the evolution of interpretation tools from the inception of SEG in 1930 to the present in 25-year increments. I have also described some possible interpretation scenarios for the year 2030, SEGs 100th Anniversary (Table 1). Obviously, I was not personally involved in interpretation in 1930 and 1955 (I was 2 years old), but I have talked with several veterans of the oil industry and reviewed numerous books and papers (especially the November 1980 issue of GEOPHYSICS which commemorates SEGs 50th Anniversary). I have been directly involved in interpretation for the 1980 and 2005 periods.

Salt Lake City 2002: A summary of the Technical program

The SEG International Exposition and Seventy-Second Annual Meeting in Salt Lake City, Utah, had more than 300 exhibitors, 630 oral and poster presentations, and an attendance of not quite 6000. In my opinion, the mood of the convention was mixed. There seemed to be significant activity for companies involved in prestack depth migration processing, special technical analyses, and some software vendors. The atmosphere was not as positive for many companies involved in seismic acquisition and related activities.

PSDM 2, The Sequel

The first special section on prestack depth migration (PSDM) was published in May 2001. The papers provided a synopsis of the state of PSDM at that time. In fact, some issues limiting greater employment of PSDM described in that special section are still prevalent today—i.e., poor data quality, improper geologic models and velocity fields, inaccurate processing algorithms, anisotropy, near surface effects, lack of true amplitude preservation, and relatively high computing costs to run the full wave equation PSDM algorithms. However, the industry has since made great strides to resolve these issues because of the rapid growth in computing power and development of more efficient migration algorithms. It was due to these advances that TLE decided to revisit this depth imaging technology and quickly publish a sequel.

An introduction to this special section: Prestack Depth Migration

In the near future, essentially all seismic data will be on depth, with time sections merely a preliminary output of the entire process of prestack depth migration.