On: “Automated identification of rock boundaries: an application of the Walsh transform to geophysical well‐log analysis” by E. N. Lanning and D. M. Johnson (GEOPHYSICS, v. 48, p. 197–205, February, 1983).

Geophysics ◽  
1984 ◽  
Vol 49 (10) ◽  
pp. 1801-1802
Author(s):  
David S. K. Chan

Lanning and Johnson’s paper presents the technique of Walsh transform domain low‐pass filtering as a means of enhancing transitions in well logs prior to boundary picking. They argue that existing fast means of computing the Walsh transform (fast Walsh transform algorithms) make this procedure particularly efficient. In this discussion it is shown that, for all practical cases of interest, the results of their paper can be obtained without any mention of the Walsh transform. In fact, using the Walsh transform unnecessarily increases computational complexity. Specifically, it is shown that the low‐pass sequency filtering described for obtaining a stepped version of the original signal with a given step width is equivalent to segmenting simply the signal into equal length segments and replacing all values in each segment by the segment average.

Geophysics ◽  
1983 ◽  
Vol 48 (2) ◽  
pp. 197-205 ◽  
Author(s):  
Eric N. Lanning ◽  
Douglas M. Johnson

A system of orthogonal functions, known as Walsh functions, which assume only the values +1 and −1, are presented as a tool appropriate for the analysis of well‐log data. Many of the characteristics of these rectangular waveforms, such as discrete transitions in signal level, make them ideal for processing borehole data. Using the generalized Fourier transform, the basic equations for the Walsh transform and Walsh power spectrum are developed showing how the energy in a given signal is distributed among these rectangular wave components. As a first application of the Walsh transform to logging data, a method of computeraided rock boundary identification is developed and demonstrated on a set of well logs from a continental basalt sequence. This technique provides a fast, simple yet accurate means of dividing well‐log data into groups of measurements corresponding to different rock units.


2018 ◽  
Author(s):  
Gulnaz Minigalieva ◽  
Albina Nigmatzyanova ◽  
Tatyana Burikova ◽  
Olga Privalova ◽  
Ruslan Akhmetzyanov ◽  
...  

2018 ◽  
Author(s):  
Gulnaz Minigalieva ◽  
Albina Nigmatzyanova ◽  
Tatyana Burikova ◽  
Olga Privalova ◽  
Ruslan Akhmetzyanov ◽  
...  

2007 ◽  
Vol 10 (06) ◽  
pp. 711-729 ◽  
Author(s):  
Paul Francis Worthington

Summary A user-friendly type chart has been constructed as an aid to the evaluation of water saturation from well logs. It provides a basis for the inter-reservoir comparison of electrical character in terms of adherence to, or departures from, Archie conditions in the presence of significant shaliness and/or low formation-water salinity. Therefore, it constitutes an analog facility. The deliverables include reservoir classification to guide well-log analysis, a protocol for optimizing the acquisition of special core data in support of log analysis, and reservoir characterization in terms of an (analog) porosity exponent and saturation exponent. The type chart describes a continuum of electrical behavior for both water and hydrocarbon zones. This is important because some reservoir rocks can conform to Archie conditions in the fully water-saturated state, but show pronounced departures from Archie conditions in the partially water-saturated state. In this respect, the chart is an extension of earlier approaches that were restricted to the water zone. This extension is achieved by adopting a generalized geometric factor—the ratio of water conductivity to formation conductivity—regardless of the degree of hydrocarbon saturation. The type chart relates a normalized form of this geometric factor to formation-water conductivity, a "shale" conductivity term, and (irreducible) water saturation. The chart has been validated using core data from comprehensively studied reservoirs. A workflow details the application of the type chart to core and/or log data. The analog role of the chart is illustrated for reservoir units that show different levels of non-Archie effects. The application of the method should take rock types, scale effects, the degree of core sampling, and net reservoir criteria into account. The principal benefit is a reduced uncertainty in the choice of a procedure for the petrophysical evaluation of water saturation, especially at an early stage in the appraisal/development process, when adequate characterizing data may not be available. Introduction One of the ever-present problems in petrophysics is how to carry out a meaningful evaluation of well logs in situations where characterizing information from quality-assured core analysis is either unavailable or is insufficient to satisfactorily support the log interpretation. This problem is especially pertinent at an early stage in the life of a field, when reservoir data are relatively sparse. Data shortfalls could be mitigated if there was a means of identifying petrophysical analogs of reservoir character, so that the broader experience of the hydrocarbon industry could be utilized in constructing reservoir models and thence be brought to bear on current appraisal and development decisions. Here, a principal requirement calls for type charts of petrophysical character, on which data from different reservoirs can be plotted and compared, as a basis for aligning approaches to future data acquisition and interpretation. This need manifests itself strongly in the petrophysical evaluation of water saturation, a process that traditionally uses the electrical properties of a reservoir rock to deliver key building blocks for an integrated reservoir model. The solution to this problem calls for an analog facility through which the electrical character of a subject reservoir can be compared with others that have been more comprehensively studied. In this way, the degree of confidence in log-derived water saturation might be reinforced. At the limit, the log analyst needs a reference basis for recourse to capillary pressure data in cases where the well-log evaluation of water saturation turns out to be prohibitively uncertain.


2021 ◽  
pp. 1-42
Author(s):  
Maheswar Ojha ◽  
Ranjana Ghosh

The Indian National Gas Hydrate Program Expedition-01 in 2006 has discovered gas hydrate in Mahanadi offshore basin along the eastern Indian margin. However, well log analysis, pressure core measurements and Infra-Red (IR) anomalies reveal that gas hydrates are distributed as disseminated within the fine-grained sediment, unlike massive gas hydrate deposits in the Krishna-Godavari basin. 2D multi-channel seismic section, which crosses the Holes NGHP-01-9A and 19B located at about 24 km apart shows a continuous bottom-simulating reflector (BSR) along it. We aim to investigate the prospect of gas hydrate accumulation in this area by integrating well log analysis and seismic methods with rock physics modeling. First, we estimate gas hydrate saturation at these two Holes from the observed impedance using the three-phase Biot-type equation (TPBE). Then we establish a linear relationship between gas hydrate saturation and impedance contrast with respect to the water-saturated sediment. Using this established relation and impedance obtained from pre-stack inversion of seismic data, we produce a 2D gas hydrate-distribution image over the entire seismic section. Gas hydrate saturation estimated from resistivity and sonic data at well locations varies within 0-15%, which agrees well with the available pressure core measurements at Hole 19. However, the 2D map of gas hydrate distribution obtained from our method shows maximum gas hydrate saturation is about 40% just above the BSR between the CDP (common depth point) 1450 and 2850. The presence of gas-charged sediments below the BSR is one of the reasons for the strong BSR observed in the seismic section, which is depicted as low impedance in the inverted impedance section. Closed sedimentary structures above the BSR are probably obstructing the movements of free-gas upslope, for which we do not see the presence of gas hydrate throughout the seismic section above the BSR.


Author(s):  
Mihir K. Sinha ◽  
Larry R. Padgett

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