HighResolution Reservoir Characterization using eNSDR

Nonstationary differential resolution: An algorithm to improve seismic resolution

Read Paper

High-resolution seismic data enables better well ties, structure delineation, stratigraphic mapping, and reservoir characterization. Differential resolution (DR) is a data-driven method to improve seismic resolution, but it can introduce a false spatial amplitude variation in the seismic output due to whole trace normalization. The newly proposed normalization technique decomposes the input seismic trace using a translating Gaussian window and then implements the DR algorithm on each window. The introduced weight factors give the interpreter control of the degree of spectral broadening. These developments enable the algorithm to account for the nonstationary properties of the seismic trace, reduce spurious spatial amplitude variation, and provide broader bandwidth seismic data for detailed analysis. We described the mathematical derivation of the nonstationary differential resolution (NSDR) algorithm and its implementation on synthetic and real seismic data. A comparison of NSDR with the original and DR shows better relative amplitude preservation.

Seismic attributes analysis and Interpretation

Seismic attributes add a new dimension to prospect evaluation and geomorphology offshore Malaysia

Read Paper

The Malay Basin is a mature Tertiary extensional basin with a later inversion regime in the Late Miocene. The general geology is simple “layer cake” seismically, with some compressive anticlinal inversion structures. The Borneo Basin, on the other hand, is tectonically complex, with steep dips, overthrust, and complex faulting. The rocks are unconsolidated, and geophysical techniques such as amplitude and other attributes should work well. In early years, seismic interpretation was based mostly on mapping structures. The advent of AVO and inversion technologies and pioneering geophysical work brought about increased usage of seismic attributes, solving various problems of geologic interpretation. In Southeast Asia, concentrated efforts since 2000 in seismic data acquisition and processing have resulted in significant improvement in data quality and hence success of attribute application. Seismic imaging and attributes meet challenges such as (1) inversion structural plays in the Malay Basin, (2) stratigraphic channels, (3) fractured basement, (4) deep high-pressure (HP) and high-temperature (HT) plays, (5) steep-dip/overthrust plays, (6) deepwater turbidite plays, (7) carbonate plays of Luconia Province, and (8) thin pay beds, often below seismic resolution, using spectral attributes. Various attributes can be applied to a widespread problem in prospect-maturation evaluation and reservoir characterization.

Artificial Intelligence and Machine Learning

Machine learning as a Silent Observer of Advance Geoscience Interpretation

Feature selection for seismic facies classification of a fluvial reservoir: Pushing the limits of spectral decomposition beyond the routine red-green-blue color blend

Enhancing Channelised Features Interpretability Using Deep Learning Predictive Modelling