Missing log data interpolation and semiautomatic seismic well ties using data matching techniques

2019 ◽  
Vol 7 (2) ◽  
pp. T347-T361 ◽  
Author(s):  
Sean Bader ◽  
Xinming Wu ◽  
Sergey Fomel
Keyword(s):  
Seismic Data ◽  
Local Similarity ◽  
Well Log ◽  
Data Set ◽  
Log Data ◽  
Data Matching ◽  
Using Data ◽  
Depth Relationship ◽  
Matching Techniques ◽  
3D Seismic Data

Relating well-log data, measured in depth, to seismic data, measured in time, typically requires estimating well-log impedance and a time-to-depth relationship using available sonic and density logs. When sonic and density logs are not available, it is challenging to incorporate wells into integrated reservoir studies because the wells cannot be tied to seismic. We have developed a workflow to estimate missing well-log information, automatically tie wells to seismic data, and generate a global well-log property volume using data matching techniques. We first used the local similarity scan to align all logs to constant geologic time and interpolate missing well-log information. Local similarity is then used to tie available wells with seismic data. Finally, log data from each well are interpolated along local seismic structures to generate global log property volumes. We use blind well tests to verify the accuracy of well-log interpolation and seismic well ties. Applying our workflow to a 3D seismic data set with 26 wells achieves consistent and verifiably accurate results.

Seismic reservoir characterization of the Bone Spring and Wolfcamp Formations in the Delaware Basin: Challenges and uncertainty in characterization using rock physics — A case study: Part 2

2020 ◽  
Vol 8 (4) ◽  
pp. T1057-T1069
Author(s):  
Ritesh Kumar Sharma ◽  
Satinder Chopra ◽  
Larry Lines
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Rock Physics ◽  
Well Log ◽  
Data Set ◽  
Frequency Model ◽  
Log Data ◽  
Delaware Basin ◽  
Seismic Reservoir

The discrimination of fluid content and lithology in a reservoir is important because it has a bearing on reservoir development and its management. Among other things, rock-physics analysis is usually carried out to distinguish between the lithology and fluid components of a reservoir by way of estimating the volume of clay, water saturation, and porosity using seismic data. Although these rock-physics parameters are easy to compute for conventional plays, there are many uncertainties in their estimation for unconventional plays, especially where multiple zones need to be characterized simultaneously. We have evaluated such uncertainties with reference to a data set from the Delaware Basin where the Bone Spring, Wolfcamp, Barnett, and Mississippian Formations are the prospective zones. Attempts at seismic reservoir characterization of these formations have been developed in Part 1 of this paper, where the geologic background of the area of study, the preconditioning of prestack seismic data, well-log correlation, accounting for the temporal and lateral variation in the seismic wavelets, and building of robust low-frequency model for prestack simultaneous impedance inversion were determined. We determine the challenges and the uncertainty in the characterization of the Bone Spring, Wolfcamp, Barnett, and Mississippian sections and explain how we overcame those. In the light of these uncertainties, we decide that any deterministic approach for characterization of the target formations of interest may not be appropriate and we build a case for adopting a robust statistical approach. Making use of neutron porosity and density porosity well-log data in the formations of interest, we determine how the type of shale, volume of shale, effective porosity, and lithoclassification can be carried out. Using the available log data, multimineral analysis was also carried out using a nonlinear optimization approach, which lent support to our facies classification. We then extend this exercise to derived seismic attributes for determination of the lithofacies volumes and their probabilities, together with their correlations with the facies information derived from mud log data.

Characterizing the regional pattern and temporal change of groundwater levels by analyses of a well log data set

2011 ◽  
Vol 5 (3) ◽  
Author(s):  
Mahmuda Parvin ◽  
Naoyuki Tadakuma ◽  
Hisafumi Asaue ◽  
Katsuaki Koike
Keyword(s):  
Temporal Change ◽  
Well Log ◽  
Regional Pattern ◽  
Data Set ◽  
Log Data ◽  
Groundwater Levels

Lithology and fluid prediction from seismic data and well log data

1993 ◽  
Author(s):  
A. W. H. Bunch ◽  
P. W. Dromgoole
Keyword(s):  
Seismic Data ◽  
Well Log ◽  
Log Data

Robust vector median filtering with a structure-adaptive implementation

Geophysics ◽  
2020 ◽  
Vol 85 (5) ◽  
pp. V407-V414
Author(s):  
Yanghua Wang ◽  
Xiwu Liu ◽  
Fengxia Gao ◽  
Ying Rao
Keyword(s):  
Seismic Data ◽  
Impulse Noise ◽  
Reservoir Characterization ◽  
Median Filter ◽  
Original Data ◽  
Thin Layers ◽  
3D Seismic ◽  
Data Set ◽  
Vector Median ◽  
3D Seismic Data

The 3D seismic data in the prestack domain are contaminated by impulse noise. We have adopted a robust vector median filter (VMF) for attenuating the impulse noise from 3D seismic data cubes. The proposed filter has two attractive features. First, it is robust; the vector median that is the output of the filter not only has a minimum distance to all input data vectors, but it also has a high similarity to the original data vector. Second, it is structure adaptive; the filter is implemented following the local structure of coherent seismic events. The application of the robust and structure-adaptive VMF is demonstrated using an example data set acquired from an area with strong sedimentary rhythmites composed of steep-dipping thin layers. This robust filter significantly improves the signal-to-noise ratio of seismic data while preserving any discontinuity of reflections and maintaining the fidelity of amplitudes, which will facilitate the reservoir characterization that follows.

Application of sparse-layer inversion and harmonic bandwidth extension for a channel system in Southern Alberta, Canada

2020 ◽  
Vol 8 (2) ◽  
pp. T217-T229
Author(s):  
Yang Mu ◽  
John Castagna ◽  
Gabriel Gil
Keyword(s):  
Seismic Data ◽  
Reflection Coefficients ◽  
3D Seismic ◽  
Bandwidth Extension ◽  
Data Set ◽  
Frequency Spectra ◽  
Channel System ◽  
Southern Alberta ◽  
Reflectivity Inversion ◽  
3D Seismic Data

Sparse-layer reflectivity inversion decomposes a seismic trace into a limited number of simple layer responses and their corresponding reflection coefficients for top and base reflections. In contrast to sparse-spike inversion, the applied sparsity constraint is less biased against layer thickness and can thus better resolve thin subtuning layers. Application to a 3D seismic data set in Southern Alberta produces inverted impedances that have better temporal resolution and lateral stability and a less blocky appearance than sparse-spike inversion. Bandwidth extension harmonically extrapolated the frequency spectra of the inverted layers and nearly doubled the usable bandwidth. Although the prospective glauconitic sand tunes at approximately 37 m, bandwidth extension reduced the tuning thickness to 22 m. Bandwidth-extended data indicate a higher correlation with synthetic traces than the original seismic data and reveal features below the original tuning thickness. After bandwidth extension, the channel top and base are more evident on inline and crossline profiles. Lateral facies changes interpreted from the inverted acoustic impedance of the bandwidth-extended data are consistent with observations in wells.

Amplitude and frequency anomalies in regional 3D seismic data surrounding the Mallik 5L-38 research site, Mackenzie Delta, Northwest Territories, Canada

Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. B183-B191 ◽  
Author(s):  
M. Riedel ◽  
G. Bellefleur ◽  
S. R. Dallimore ◽  
A. Taylor ◽  
J. F. Wright
Keyword(s):  
Northwest Territories ◽  
Gas Hydrate ◽  
Seismic Data ◽  
Ratio Method ◽  
Unfrozen Water ◽  
3D Seismic ◽  
Mackenzie Delta ◽  
Data Set ◽  
Seismic Amplitude ◽  
3D Seismic Data

Amplitude and frequency anomalies associated with lakes and drainage systems were observed in a 3D seismic data set acquired in the Mallik area, Mackenzie Delta, Northwest Territories, Canada. The site is characterized by large gas hydrate deposits inferred from well-log analyses and coring. Regional interpretation of the gas hydrate occurrences is mainly based on seismic amplitude anomalies, such as brightening or blanking of seismic energy. Thus, the scope of this research is to understand the nature of the amplitude behavior in the seismic data. We have therefore analyzed the 3D seismic data to define areas with amplitude reduction due to contamination from lakes and channels and to distinguish them from areas where amplitude blanking may be a geologic signal. We have used the spectral ratio method to define attenuation (Q) over different areas in the 3D volume and subsequently applied Q-compensation to attenuate lateral variations ofdispersive absorption. Underneath larger lakes, seismic amplitude is reduced and the frequency content is reduced to [Formula: see text], which is half the original bandwidth. Traces with source-receiver pairs located inside of lakes show an attenuation factor Q of [Formula: see text], approximately half of that obtained for source-receiver pairs situated on deep, continuous permafrost outside of lakes. Deeper reflections occasionally identified underneath lakes show low-velocity-related pull-down. The vertical extent of the washout zones is enhanced by acquisition with limited offsets and from processing parameters such as harsh mute functions to reduce noise from surface waves. The strong attenuation and seismic pull-down may indicate the presence of unfrozen water in deeper lakes and unfrozen pore water within the sediments underlying the lakes. Thus, the blanking underneath lakes is not necessarily related to gas migration or other in situ changes in physical properties potentially associated with the presence of gas hydrate.

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