Browsing by Subject "Seismic attributes"

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Depth-registration of 9-component 3-dimensional seismic data in Stephens County, Oklahoma
(2014-05) Al-Waily, Mustafa Badieh; Hardage, Bob Adrian, 1939-
Multicomponent seismic imaging techniques improve geological interpretation by providing crucial information about subsurface characteristics. These techniques deliver different images of the same subsurface using multiple waveforms. Compressional (P) and shear (S) waves respond to lithology and fluid variations differently, providing independent measurements of rock and fluid properties. Joint interpretation of multicomponent images requires P-wave and S-wave events to be aligned in depth. The process of identifying P and S events from the same reflector is called depth-registration. The purpose of this investigation is to illustrate procedures for depth-registering P and S seismic data when the most fundamental information needed for depth-registration – reliable velocity data – are not available. This work will focus on the depth-registration of a 9-component 3-dimensional seismic dataset targeting the Sycamore formation in Stephens County, Oklahoma. The survey area – 16 square miles – is located in Sho-Vel-Tum oilfield. Processed P-P, SV-SV, and SH-SH wave data are available for post-stack analysis. However, the SV-data volume will not be interpreted because of its inferior data-quality compared to the SH-data volume. Velocity data are essential in most depth-registration techniques: they can be used to convert the seismic data from the time domain to the depth domain. However, velocity data are not available within the boundaries of the 9C/3D seismic survey. The data are located in a complex area that is folded and faulted in the northwest part of the Ardmore basin, between the eastern Arbuckle Mountains and the western Wichita Mountains. Large hydrocarbon volumes are produced from stratigraphic traps, fault closures, anticlines, and combination traps. Sho-Vel-Tum was ranked 31st in terms of proved oil reserves among U.S. oil fields by a 2009 survey. I will interpret different depth-registered horizons on the P-wave and S-wave seismic data volumes. Then, I will present several methods to verify the accuracy of event-registration. Seven depth-registered horizons are mapped through the P-P and SH-SH seismic data. These horizons show the structural complexity that imposes serious challenges on well drilling within the Sho-Vel-Tum oil field. Interval Vp/Vs – a seismic attribute often used as lithological indicator – was mapped to constrain horizon picking and to characterize lateral stratigraphic variations.
Gas-hydrates saturation estimation in Krishna-Godavari basin, India
(2013-05) Das, Kumar Sundaram; Sen, Mrinal K.; Tatham, Robert; Spikes, Kyle
Gas hydrates are an unconventional energy resource. They may become an important source of energy for India in the future. They occur offshore along the continental margin. They are currently in exploratory and evaluation stages and their quantification is an important task. The goal of this thesis is to demonstrate a new technique for the estimation of gas hydrates volumes. The region of study is the Krishna-Godavari basin. It is located on the eastern offshore areas of India. The presence of gas hydrates has been proven by drilling into marine sediments as a part of the Indian National Gas Hydrates Program. Borehole subsurface and surface seismic data were collected during this expedition. I use a 2D seismic reflection line and borehole log data for my study. The method I use for estimation of gas hydrates saturation uses a combination of inversion of seismic reflection data and development of seismic attributes. My approach can be broadly described by following steps: 1. Process the seismic data to remove noise. Use stacked and migrated data along with well logs to perform poststack seismic inversion to obtain impedance information in volumetric portions of the subsurface. 2. Use NMO corrected CDP gather records of the seismic reflection data along with subsurface well logs to perform prestack seismic inversion to obtain impedance volumes. 3. Compare the results from step1 and step 2 and use the best results to perform multi-attribute analysis using a neural network method to predict resistivity and porosity logs at the well location. Use the transform equations obtained at the well location to predict the well logs throughout the seismic section in the desired zone of interest. 4. Use an anisotropic equivalent of Archie’s law that relates resistivity and porosity to saturation to predict saturation throughout the seismic reflection section. The majority of the previous work done in the region is limited to gas hydrates quantification only at the well location. By using neural networks for multi-attribute analysis, I have demonstrated a statistical based method for the prediction of log properties away from well location. My results suggest gas hydrates saturation in the range of 50-80% in the zone of interest. The estimated saturation of gas hydrates matches up very closely with the saturation estimates obtained from the cores recovered during coring of the boreholes. Hence my method provides a reliable method of quantification of gas hydrates by making best possible use of seismic and well log data. The unique combination of impedance derived attributes and neural-network includes the non-linear behavior in the predictive transform relationships. The use of an anisotropic formulation of Archie’s law to estimate saturation also produces accurate results confirmed with the observed gas-hydrates saturation.