Estimation of effective porosity using geostatistics and multiattribute transforms: A case study

Geophysics ◽  
2004 ◽  
Vol 69 (2) ◽  
pp. 352-372 ◽  
Author(s):  
A. G. Pramanik ◽  
V. Singh ◽  
Rajiv Vig ◽  
A. K. Srivastava ◽  
D. N. Tiwary
Keyword(s):  
Seismic Data ◽  
Acoustic Impedance ◽  
Reservoir Characterization ◽  
Middle Eocene ◽  
Seismic Attributes ◽  
Effective Porosity ◽  
3D Seismic ◽  
Porosity Distribution ◽  
Porosity Logs ◽  
3D Seismic Data

The middle Eocene Kalol Formation in the north Cambay Basin of India is producing hydrocarbons in commercial quantity from a series of thin clastic reservoirs. These reservoirs are sandwiched between coal and shale layers, and are discrete in nature. The Kalol Formation has been divided into eleven units (K‐I to K‐XI) from top to bottom. Multipay sands of the K‐IX unit 2–8 m thick are the main hydrocarbon producers in the study area. Apart from their discrete nature, these sands exhibit lithological variation, which affects the porosity distribution. Low‐porosity zones are found devoid of hydrocarbons. In the available 3D seismic data, these sands are not resolved and generate a composite detectable seismic response, making reservoir characterization through seismic attributes impossible. After proper well‐to‐seismic tie, the major stratigraphic markers were tracked in the 3D seismic data volume for structural mapping and carrying out attribute analysis. The 3D seismic volume was inverted to obtain an acoustic impedance volume using a model‐based inversion algorithm, improving the vertical resolution and resolving the K‐IX pay sands. For better reservoir characterization, effective porosity distribution was estimated through different available techniques taking the K‐IX upper sand as an example. Various sample‐based seismic attributes, the impedance volume, and effective porosity logs were used as inputs for this purpose. These techniques are map‐based geostatistical methods using the acoustic impedance volume, stepwise multilinear regression, probabilistic neural networks (PNN) using multiattribute transforms, and a new technique that incorporates both geostatistics and multiattribute transforms (either linear or nonlinear). This paper is an attempt to compare different available techniques for porosity estimation. On comparison, it is found that the PNN‐based approach using ten sample‐based attributes showed highest crosscorrelation (0.9508) between actual and predicted effective porosity logs at eight wells in the study area. After validation, the predicted effective porosity maps for the K‐IX upper sand are generated using different techniques, and a comparison among them is made. The predicted effective porosity map obtained from PNN‐based model provides more meaningful information about the K‐IX upper sand reservoir. In order to give priority to the actual effective porosity values at wells, the predicted effective porosity map obtained from PNN‐based model for the K‐IX upper sand was combined with actual effective porosity values using co‐kriging geostatistical technique. This final map provides geologically more realistic predicted effective porosity distribution and helps in understanding the subsurface image. The implication of this work in exploration and development of hydrocarbons in the study area is discussed.

scholarly journals Evaluation of seismic attributes for reservoir characterization over Edi field, Niger delta, Nigeria using 3d seismic data

2020 ◽  
Vol 8 (2) ◽  
pp. 168
Author(s):  
Nyeneime O. Etuk ◽  
Mfoniso U. Aka ◽  
Okechukwu A. Agbasi ◽  
Johnson C. Ibuot
Keyword(s):  
Seismic Data ◽  
Niger Delta ◽  
Reservoir Characterization ◽  
Seismic Attributes ◽  
3D Seismic ◽  
Root Mean Square Amplitude ◽  
Phase Gradient ◽  
Major Fault ◽  
Seismic Sections ◽  
3D Seismic Data

Seismic attributes were evaluated over Edi field, offshore Western Niger Delta, Nigeria, via 3D seismic data. Manual mappings of the horizons and faults on the in-lines and cross-lines of the seismic sections were done. Various attributes were calculated and out put on four horizons corresponding to the well markers at different formations within the well were identified. The four horizons identified, which includes: H1, H2, H3 and H4 were mapped and interpreted across the field. The operational agenda was thru picking given faults segments on the in–line of seismic volume. A total of five faults coded as F1, F2, F3, F4 and F5, F1 and F5 were the major fault and were observed as extending through the field. Structural and horizon mappings were used to generate time structure maps. The maps showed the various positions and orientations of the faults. Different attributes which include: root mean square amplitude, instantaneous phase, gradient magnitude and chaos were run on the 3D seismic data. The amplitude and incline magnitude maps indicate direct hydrocarbon on the horizon maps; this is very important in the drilling of wells because it shows areas where hydrocarbons are present in the subsurface. The seismic attributes revealed information, which was not readily apparent in the raw seismic data.   

scholarly journals Use of Attributes on 3D Seismic Data for Studying Mishrif Formation in East Abu-Amoud Field, South-Eastern Iraq

2021 ◽  
pp. 4802-4809
Author(s):  
Mohammed H. Al-Aaraji ◽  
Hussein H. Karim
Keyword(s):  
Seismic Data ◽  
Acoustic Impedance ◽  
Seismic Attributes ◽  
3D Seismic ◽  
Seismic Section ◽  
Reflected Waves ◽  
South Eastern ◽  
Seismic Sections ◽  
Sonic Logs ◽  
3D Seismic Data

      The seismic method depends on the nature of the reflected waves from the interfaces between layers, which in turn depends on the density and velocity of the layer, and this is called acoustic impedance. The seismic sections of the East Abu-Amoud field that is located in Missan Province, south-eastern Iraq, were studied and interpreted for updating the structural picture of the major Mishrif Formation for the reservoir in the field. The Mishrif Formation is rich in petroleum in this area, with an area covering about 820 km2. The horizon was calibrated and defined on the seismic section with well logs data (well tops, check shot, sonic logs, and density logs) in the interpretation process to identify the upper and lower boundaries of the Formation.  Seismic attributes were used to study the formation, including instantaneous phase attributes and relative acoustic impedance on time slice of 3D seismic data . Also, relative acoustic impedance was utilized to study the top of the Mishrif Formation. Based on these seismic attributes, karst features of the formation were identified. In addition, the nature of the lithology in the study area and the change in porosity were determined through the relative acoustic impedance The overlap of the top of the Mishrif Formation with the bottom of the Khasib Formation was determined because the Mishrif Formation is considered as an unconformity surface.

Unsupervised machine learning using 3D seismic data applied to reservoir evaluation and rock type identification

2021 ◽  
pp. 1-69
Author(s):  
Marwa Hussein ◽  
Robert R. Stewart ◽  
Deborah Sacrey ◽  
Jonny Wu ◽  
Rajas Athale
Keyword(s):  
Machine Learning ◽  
Seismic Data ◽  
Rock Type ◽  
Seismic Attributes ◽  
Reservoir Quality ◽  
3D Seismic ◽  
Reservoir Properties ◽  
Unsupervised Machine Learning ◽  
Amplitude Data ◽  
3D Seismic Data

Net reservoir discrimination and rock type identification play vital roles in determining reservoir quality, distribution, and identification of stratigraphic baffles for optimizing drilling plans and economic petroleum recovery. Although it is challenging to discriminate small changes in reservoir properties or identify thin stratigraphic barriers below seismic resolution from conventional seismic amplitude data, we have found that seismic attributes aid in defining the reservoir architecture, properties, and stratigraphic baffles. However, analyzing numerous individual attributes is a time-consuming process and may have limitations for revealing small petrophysical changes within a reservoir. Using the Maui 3D seismic data acquired in offshore Taranaki Basin, New Zealand, we generate typical instantaneous and spectral decomposition seismic attributes that are sensitive to lithologic variations and changes in reservoir properties. Using the most common petrophysical and rock typing classification methods, the rock quality and heterogeneity of the C1 Sand reservoir are studied for four wells located within the 3D seismic volume. We find that integrating the geologic content of a combination of eight spectral instantaneous attribute volumes using an unsupervised machine-learning algorithm (self-organizing maps [SOMs]) results in a classification volume that can highlight reservoir distribution and identify stratigraphic baffles by correlating the SOM clusters with discrete net reservoir and flow-unit logs. We find that SOM classification of natural clusters of multiattribute samples in the attribute space is sensitive to subtle changes within the reservoir’s petrophysical properties. We find that SOM clusters appear to be more sensitive to porosity variations compared with lithologic changes within the reservoir. Thus, this method helps us to understand reservoir quality and heterogeneity in addition to illuminating thin reservoirs and stratigraphic baffles.

scholarly journals Characterization of reservoir sands using 3D seismic attributes in the coastal swamp area of Niger Delta Basin

2021 ◽  
Author(s):  
Oluwatoyin Khadijat Olaleye ◽  
Pius Adekunle Enikanselu ◽  
Michael Ayuk Ayuk
Keyword(s):  
Seismic Data ◽  
Niger Delta ◽  
Seismic Attributes ◽  
Effective Porosity ◽  
High Porosity ◽  
Hydrocarbon Accumulation ◽  
3D Seismic ◽  
Seismic Attribute ◽  
Niger Delta Basin

AbstractHydrocarbon accumulation and production within the Niger Delta Basin are controlled by varieties of geologic features guided by the depositional environment and tectonic history across the basin. In this study, multiple seismic attribute transforms were applied to three-dimensional (3D) seismic data obtained from “Reigh” Field, Onshore Niger Delta to delineate and characterize geologic features capable of harboring hydrocarbon and identifying hydrocarbon productivity areas within the field. Two (2) sand units were delineated from borehole log data and their corresponding horizons were mapped on seismic data, using appropriate check-shot data of the boreholes. Petrophysical summary of the sand units revealed that the area is characterized by high sand/shale ratio, effective porosity ranged from 16 to 36% and hydrocarbon saturation between 72 and 92%. By extracting attribute maps of coherence, instantaneous frequency, instantaneous amplitude and RMS amplitude, characterization of the sand units in terms of reservoir geomorphological features, facies distribution and hydrocarbon potential was achieved. Seismic attribute results revealed (1) characteristic patterns of varying frequency and amplitude areas, (2) major control of hydrocarbon accumulation being structural, in terms of fault, (3) prospective stratigraphic pinch-out, lenticular thick hydrocarbon sand, mounded sand deposit and barrier bar deposit. Seismic Attributes analysis together with seismic structural interpretation revealed prospective structurally high zones with high sand percentage, moderate thickness and high porosity anomaly at the center of the field. The integration of different seismic attribute transforms and results from the study has improved our understanding of mapped sand units and enhanced the delineation of drillable locations which are not recognized on conventional seismic interpretations.

Geostatistical reservoir characterization constrained by 3D seismic data

1998 ◽  
Vol 4 (2) ◽  
pp. 121-128 ◽  
Author(s):  
O. Dubrule ◽  
M. Thibaut ◽  
P. Lamy ◽  
A. Haas
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
3D Seismic ◽  
3D Seismic 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.

Identification of polygonal faulting from legacy 3D seismic data in vintage Gulf of Mexico data using seismic attributes

2021 ◽  
pp. 1-17
Author(s):  
Karen M. Leopoldino Oliveira ◽  
Heather Bedle ◽  
Karelia La Marca Molina
Keyword(s):  
Seismic Data ◽  
Seismic Attributes ◽  
Fault System ◽  
3D Seismic ◽  
Seismic Attribute ◽  
Variable Amplitude ◽  
Attribute Analysis ◽  
Amplitude Data ◽  
3D Seismic Data ◽  
Polygonal Fault

We analyzed a 1991 3D seismic data located offshore Florida and applied seismic attribute analysis to identify geological structures. Initially, the seismic data appears to have a high signal-to-noise-ratio, being of an older vintage of quality, and appears to reveal variable amplitude subparallel horizons. Additional geophysical analysis, including seismic attribute analysis, reveals that the data has excessive denoising, and that the continuous features are actually a network of polygonal faults. The polygonal faults were identified in two tiers using variance, curvature, dip magnitude, and dip azimuth seismic attributes. Inline and crossline sections show continuous reflectors with a noisy appearance, where the polygonal faults are suppressed. In the variance time slices, the polygonal fault system forms a complex network that is not clearly imaged in the seismic amplitude data. The patterns of polygonal fault systems in this legacy dataset are compared to more recently acquired 3D seismic data from Australia and New Zealand. It is relevant to emphasize the importance of seismic attribute analysis to improve accuracy of interpretations, and also to not dismiss older seismic data that has low accurate imaging, as the variable amplitude subparallel horizons might have a geologic origin.

Improved structural interpretation of legacy 3D seismic data from Karee platinum mine (South Africa) through the application of novel seismic attributes

2019 ◽  
Vol 68 (1) ◽  
pp. 145-163 ◽  
Author(s):  
Musa S.D. Manzi ◽  
Gordon R.J. Cooper ◽  
Alireza Malehmir ◽  
Raymond J. Durrheim
Keyword(s):  
South Africa ◽  
Seismic Data ◽  
Seismic Attributes ◽  
3D Seismic ◽  
Structural Interpretation ◽  
3D Seismic Data
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