Discrete 3D fracture network extraction and characterization from 3D seismic data — A case study at Teapot Dome

2015 ◽  
Vol 3 (3) ◽  
pp. ST29-ST41 ◽  
Author(s):  
Manoj Vallikkat Thachaparambil
Keyword(s):  
Seismic Data ◽  
Seismic Attributes ◽  
3D Seismic ◽  
Spectral Edge ◽  
Teapot Dome ◽  
Fracture Data ◽  
Discontinuity Surfaces ◽  
Seismic Discontinuity ◽  
3D Seismic Data ◽  
Tensleep Formation

Three-dimensional discrete fracture networks (DFNs) extracted from the seismic data of the Tensleep Formation at Teapot Dome successfully matched 1D fracture data from multiple boreholes within the area. The extraction process used four seismic attributes, i.e., variance, chaos, curvature, and spectral edge, and their multiple realizations to define seismic discontinuities that could potentially represent fractures within the Tensleep Formation. All of the potential fracture attributes were further enhanced using a fracture-tracking attribute for better extraction and analysis of seismic discontinuity surfaces and their network properties. A state-of-the-art discontinuity surface extraction and characterization workflow uniformly extracted and interactively characterized the seismic discontinuity surfaces and networks that correlate with borehole fracture data. Among the attributes, a fracture-tracking attribute cube created out of the high-resolution spectral-edge attribute provided the best match with the borehole fracture data from the Tensleep Formation. Therefore, the extracted discontinuity planes were classified as fractures and then characterized. The extracted fracture population also matched earlier published records of faults and fractures at Teapot Dome. Unlike the conventional method, which uses 1D borehole fracture data as primary input and 3D seismic data as a guide volume during DFN modeling, I used 3D seismic attributes as the primary data and the 1D borehole fracture data only for quality control. I also evaluated the power of converting seismic fracture attribute volumes into discrete surfaces and networks for effective correlation with 1D fracture logs from boreholes.

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 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.   

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.

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.

Reservoir characterization using microseismic facies analysis integrated with surface seismic attributes

2016 ◽  
Vol 4 (2) ◽  
pp. T167-T181 ◽  
Author(s):  
Aamir Rafiq ◽  
David W. Eaton ◽  
Adrienne McDougall ◽  
Per Kent Pedersen
Keyword(s):  
Seismic Data ◽  
Principal Curvature ◽  
Facies Analysis ◽  
Shape Index ◽  
Seismic Attributes ◽  
Seismic Survey ◽  
3D Seismic ◽  
Frequency Distributions ◽  
Scaling Properties ◽  
3D Seismic Data

We have developed the concept of microseismic facies analysis, a method that facilitates partitioning of an unconventional reservoir into distinct facies units on the basis of their microseismic response along with integrated interpretation of microseismic observations with 3D seismic data. It is based upon proposed links between magnitude-frequency distributions and scaling properties of reservoirs, including the effects of mechanical bed thickness and stress heterogeneity. We evaluated the method using data from hydraulic fracture monitoring of a Late Cretaceous tight sand reservoir in central Alberta, in which microseismic facies can be correlated with surface seismic attributes (primarily principal curvature, coherence, and shape index) from a coincident 3D seismic survey. Facies zones are evident on the basis of attribute crossplots, such as maximum moment release rate versus cluster azimuth. The microseismically defined facies correlate well with principal curvature anomalies from 3D seismic data. By combining microseismic facies analysis with regional trends derived from log and core data, we delineate reservoir partitions that appear to reflect structural and depositional trends.

The Application of Seismic Attribute in the Prediction of Inner Front Facies Sands

2012 ◽  
Vol 616-618 ◽  
pp. 705-709
Author(s):  
Kai Chun Yu ◽  
Yan Zhu ◽  
Yan Meng
Keyword(s):  
Comparative Analysis ◽  
Seismic Data ◽  
Prediction Accuracy ◽  
Seismic Attributes ◽  
Small River ◽  
3D Seismic ◽  
Seismic Attribute ◽  
Well Spacing ◽  
Reservoir Description ◽  
3D Seismic Data

The south of Daqing placanticline is mainly front facies reservoir which is chiefly the smooth, direct, narrow and small river. The size of the river is small and the reservoir thickness is mainly 1.0m-1.2m.The prediction accuracy of the interwell sandbody is only up to 60~70% under the condition of existing well network and well spacing, causing the relatively worse development effect. In order to raise the prediction accuracy of the interwell sandbody, it proposes the thinking of identifying the boundary and orientation of the inner front facies by means of the combination of wells and seismos of 3D seismic data. After the comparative analysis of the wells and the seismos, it determines the seismic attributes which can reflect the sandstone and identify mudstone preferablely, and proposes the method of reservoir description by means of the combination of wells and seismos which makes the prediction accuracy of the interwell sandbody reach to 80.77%.

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.

Characterization of a fracture zone using seismic attributes at the In Salah CO2 storage project

2015 ◽  
Vol 3 (2) ◽  
pp. SM37-SM46 ◽  
Author(s):  
Rui Zhang ◽  
Donald Vasco ◽  
Thomas M. Daley ◽  
William Harbert
Keyword(s):  
Carbon Dioxide ◽  
Fracture Zone ◽  
Seismic Data ◽  
Co2 Storage ◽  
Seismic Attributes ◽  
3D Seismic ◽  
Lower Velocity ◽  
Surface Uplift ◽  
3D Seismic Data

The In Salah carbon dioxide storage project in Algeria has injected more than 3 million tons of carbon dioxide into a water-filled tight-sand formation. During injection, interferometric synthetic aperture radar (InSAR) reveals a double-lobed pattern of up to a 20-mm surface uplift above the horizontal leg of an injection well. Interpretation of 3D seismic data reveals the presence of a subtle linear push-down feature located along the InSAR determined surface depression between the two lobes, which we interpreted to have to be caused by anomalously lower velocity from the fracture zone and the presence of [Formula: see text] displacing brine in this feature. To enhance the seismic interpretation, we calculated many poststack seismic attributes, including positive and negative curvatures as well as ant track, from the 3D seismic data. The maximum positive curvature attributes and ant track found the clearest linear features, with two parallel trends, which agreed well with the ant-track volume and the InSAR observations of the depression zone. The seismic attributes provided a plausible characterization of the fracture zone extent, including height, width, and length (80, 350, and 3500 m, respectively), providing important information for further study of fracture behavior due to the [Formula: see text] injection at In Salah. We interpreted the pattern of depression between two surface-deformation lobes as caused by the opening of a subvertical fracture or damage zone at depth above the injection interval, which allowed injected [Formula: see text] to migrate upward. Our analysis corroborated previous interpretation of surface uplift as due to the injection of [Formula: see text] in this well.

Analysis of Oil-Volume Fluxes of Hydrocarbon-Seep Formations on the Green Canyon and Mississippi Canyon: A Study With 3D-Seismic Attributes in Combination With Satellite and Acoustic Data

2014 ◽  
Vol 17 (04) ◽  
pp. 430-435 ◽  
Author(s):  
Oscar Garcia-Pineda ◽  
Ian MacDonald ◽  
William Shedd
Keyword(s):  
Deep Water ◽  
Seismic Data ◽  
Seismic Attributes ◽  
3D Seismic ◽  
Sar Images ◽  
Acoustic Data ◽  
Oil Seeps ◽  
Mississippi Canyon ◽  
Geophysical Anomalies ◽  
3D Seismic Data

Summary Natural hydrocarbon seeps have an important role in the carbon cycle and in the Gulf of Mexico (GOM) ecosystem. The magnitude of these natural oil seeps was analyzed with 3D-seismic attributes in combination with satellite and acoustic data. Hydrocarbon seepage in the deep water of the GOM is associated with deep cutting faults, generated by vertical salt movement, that provide conduits for the upward migration of oil and gas. Seeps transform surface geology and generate prominent geophysical targets that can be identified in 3D-seismic data. Seafloor-amplitude anomalies in plain view correlate with the underlying fault systems. On the basis of 3D-seismic data, detailed mapping of the northern GOM has identified more than 24,000 geophysical anomalies across the basin. In addition to seismic data, synthetic-aperture-radar (SAR) images have proved to be a reliable tool for localizing natural seepage of oil. We used a texture-classifier neural-network algorithm (TCNNA) to process more than 1,200 SAR images collected over the GOM. We quantified more than 1,000 individual seep formations distributed along the outer continental shelf and in deep water. Comparison of the geophysical anomalies with the SAR oil-slick targets shows good general agreement between the distributions of the two indicators. However, there are far fewer active oil seeps than geophysical anomalies, probably because of timing constraints during the basin evolution. Studying the size of the oil slicks on the surface (normalized to weather conditions), we found that the average flux rate of oil (per seep) may be affected by the local change in the baroclinic and barotrophic pressures [e.g., warm core eddies (WCEs) and storms]. We found that oil slicks in the Mississippi Canyon (MC) protraction area tend to be more sensitive to pressure changes than Green Canyon (GC) protraction-area seeps.

Sign in / Sign up

Export Citation Format

Share Document