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.

scholarly journals APPLYING FILTERS AND SEISMIC ATTRIBUTES FOR ENHANCING FAULTS IN THE 3D SEISMIC SURVEY OF ALTO DE SIRIRIZINHO (SERGIPE-ALAGOAS BASIN, NORTHEAST BRAZIL)

2013 ◽  
Vol 31 (1) ◽  
pp. 109
Author(s):  
Arthur Victor Medeiros Francelino ◽  
Alex Francisco Antunes
Keyword(s):  
Seismic Data ◽  
Median Filter ◽  
Random Noise ◽  
Seismic Attributes ◽  
Oil Fields ◽  
Seismic Survey ◽  
Northeast Brazil ◽  
3D Seismic ◽  
3D Seismic Data

The 3D seismic data allow that mature oil fields be reevaluated in order to improve the characterization of faults that affect the flow of hydrocarbons. The use of seismic attributes and filtering allows an improvement in the identification and enhancement of these fractures on seismic data. In this study, we used two different filters: the dip-steered median filter to remove random noise and increase the lateral continuity of reflections, and the fault-enhancement filter used to enhance the discontinuities of the reflections. After filtering, similarity and curvature attributes were applied in order to identify the distribution of fractures along the data. Theuse of these attributes and filters contributed greatly to the identification and enhancement of the continuity of the fractures. RESUMO: Com o advento da sísmica 3D, campos de petróleo maduros podem ser reavaliados melhorando a caracterização das falhas que influenciam o fluxo de hidrocarbonetos. A utilização de filtragens e atributos sísmicos possibilita uma melhora na identificação e no realce dessas fraturas no dado sísmico. No presente trabalho foram utilizados dois tipos de filtros, sendo o dip-steered median filter, com a finalidade de retirar os ruídos aleatórios e aumentar a continuidade lateral das reflexões, e o fault-enhancement filter para realçar as descontinuidades das reflexões. Após a etapa de filtragem foram aplicados os atributos de similaridade e curvatura, para se identificar a distribuição das falhas. O uso dos atributos e filtragens colaborou fortemente para a identificação e o realce da continuidade das fraturas. Palavras-chave: reservatório fraturado; interpretação sísmica e atributos sísmicos

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.

scholarly journals CO2 storage monitoring: leakage detection and measurement in subsurface volumes from 3D seismic data at Sleipner

2014 ◽  
Vol 63 ◽  
pp. 4224-4239 ◽  
Author(s):  
R. Andrew Chadwick ◽  
Benjamin P. Marchant ◽  
Gareth A. Williams
Keyword(s):  
Seismic Data ◽  
Co2 Storage ◽  
3D Seismic ◽  
Leakage Detection ◽  
3D Seismic Data

Time-lapse analysis of sparse 3D seismic data from the CO2 storage pilot site at Ketzin, Germany

2012 ◽  
Vol 84 ◽  
pp. 14-28 ◽  
Author(s):  
Monika Ivandic ◽  
Can Yang ◽  
Stefan Lüth ◽  
Calin Cosma ◽  
Christopher Juhlin
Keyword(s):  
Seismic Data ◽  
Co2 Storage ◽  
Time Lapse ◽  
3D Seismic ◽  
Pilot Site ◽  
3D Seismic Data

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.

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