Use of 3D Seismic Attributes and Well Data for Shale Pressure Cube Prediction in Silicoclastic Domain - Two Case Studies

2017 ◽  
Author(s):  
C. Colle ◽  
T. Vidaillac ◽  
B. Benazet ◽  
F. Peoymarie
Keyword(s):  
Case Studies ◽  
Seismic Attributes ◽  
3D Seismic ◽  
Well Data

Fracture detection using multi seismic attributes ant-tracking in the Rag-e-Sefid oilfield, SW Iran

2021 ◽  
Author(s):  
Zahra Tajmir Riahi ◽  
Khalil Sarkarinejad ◽  
Ali Faghih ◽  
Bahman Soleimany ◽  
Gholam Reza Payrovian
Keyword(s):  
Seismic Data ◽  
Large Scale ◽  
Seismic Attributes ◽  
Structural Features ◽  
Hydrocarbon Exploration ◽  
Small Scale ◽  
Northwestern Part ◽  
3D Seismic ◽  
Petroleum Reservoir ◽  
Well Data

<p><strong>Abstract</strong></p><p>The detailed characterization of faults and fractures can give valuable information about the fluid flow through petroleum reservoir and directly affect the hydrocarbon exploration and production programs. In this study, large- and small-scale fractures in the Asmari horizon of the Rag-e-Sefid oilfield were characterized using seismic attribute and well data analyses. Different spatial filters including finite median hybrid (SO-FMH), dip-steered median, dip-steered diffusion, and fault enhancement filters were used on 3D seismic data to reduce noise, enhance the seismic data quality, and create a 3D seismic steering cube. In the next step, seismic attributes such as coherency, similarity, variance, spectral decomposition, dip, and curvature were applied to identify structural features. In order to check the validity of these structural features, results from seismic attributes calibrated by the interpreted fractures from image logs in the Rag-e-Safid oilfield. Then, the ant-tracking algorithm applied on the selected seismic attributes to highlight faults and fractures. These attributes combined using neural network method to create multi-seismic attributes, view different fault- or fold-sensitive seismic attributes in a single image, and facilitate the large-scale fractures extraction process. Finally, automatic fault and fracture extraction technique used to reduce human intervention, improve accuracy and efficiency for the large-scale fracture interpretation and extraction from edge volumes in the Asmari horizon of the Rag-e-Sefid oilfield. In addition to, small- scale fractures were characterized by the obtained information from the image logs interpretation for sixteen wells. All the detected fractures from seismic and well data have been divided into eight fracture sets based on their orientation and using the statistical analysis. The obtained results show that fractures characteristics and their origin are different in the northwestern and southeastern parts of the Rag-e-Sefid oilfield. The NW Rag-e-Sefid and Nourooz Hendijan Izeh Faults reactivation during Zagros orogeny led to create the dextral shear zone and P, R, R′, T, Y- fracture sets in the northwestern part of the Rag-e-Safid oilfield. Also, activity of the SE-Rag-e-Sefid thrust fault during Zagros orogeny caused to form fault-related fractures sets in the southeastern part of the Rag-e-Sefid field. In addition to, axial, cross axial, oblique fracture sets in the Asmari horizon of the Rag-e-Sefid oilfield were created by folding phase during Zagros orogeny. The obtained results were used to fracture modeling in the Asmari horizon of the Rag-e-Sefid oilfield.</p>

scholarly journals Geomorphological Geometries and High-Resolution Seismic Sequence Stratigraphy of Malay Basin’s Fluvial Succession

2021 ◽  
Vol 11 (11) ◽  
pp. 5156
Author(s):  
Abd Al-Salam Al-Masgari ◽  
Mohamed Elsaadany ◽  
Numair A. Siddiqui ◽  
Abdul Halim Abdul Latiff ◽  
Azli Abu Bakar ◽  
...  
Keyword(s):  
High Resolution ◽  
Sequence Stratigraphy ◽  
Three Dimensional ◽  
Seismic Attributes ◽  
Seismic Facies ◽  
Seismic Sequence ◽  
3D Seismic ◽  
Seismic Sequences ◽  
Seismic Sequence Stratigraphy ◽  
Point Bars

This study identified the Pleistocene depositional succession of the group (A) (marine, estuarine, and fluvial depositional systems) of the Melor and Inas fields in the central Malay Basin from the seafloor to approximately −507 ms (522 m). During the last few years, hydrocarbon exploration in Malay Basin has moved to focus on stratigraphic traps, specifically those that existed with channel sands. These traps motivate carrying out this research to image and locate these kinds of traps. It can be difficult to determine if closely spaced-out channels and channel belts exist within several seismic sequences in map-view with proper seismic sequence geomorphic elements and stratigraphic surfaces seismic cross lines, or probably reinforce the auto-cyclic aggregational stacking of the avulsing rivers precisely. This analysis overcomes this challenge by combining well-log with three-dimensional (3D) seismic data to resolve the deposition stratigraphic discontinuities’ considerable resolution. Three-dimensional (3D) seismic volume and high-resolution two-dimensional (2D) seismic sections with several wells were utilized. A high-resolution seismic sequence stratigraphy framework of three main seismic sequences (3rd order), four Parasequences sets (4th order), and seven Parasequences (5th order) have been established. The time slice images at consecutive two-way times display single meandering channels ranging in width from 170 to 900 m. Moreover, other geomorphological elements have been perfectly imaged, elements such as interfluves, incised valleys, chute cutoff, point bars, and extinction surfaces, providing proof of rapid growth and transformation of deposits. The high-resolution 2D sections with Cosine of Phase seismic attributes have facilitated identifying the reflection terminations against the stratigraphic amplitude. Several continuous and discontinuous channels, fluvial point bars, and marine sediments through the sequence stratigraphic framework have been addressed. The whole series reveals that almost all fluvial systems lay in the valleys at each depositional sequence’s bottom bars. The degradational stacking patterns are characterized by the fluvial channels with no evidence of fluvial aggradation. Moreover, the aggradation stage is restricted to marine sedimentation incursions. The 3D description of these deposits permits distinguishing seismic facies of the abandoned mud channel and the sand point bar deposits. The continuous meandering channel, which is filled by muddy deposits, may function as horizontal muddy barriers or baffles that might isolate the reservoir body into separate storage containers. The 3rd, 4th, and 5th orders of the seismic sequences were established for the studied succession. The essential geomorphological elements have been imaged utilizing several seismic attributes.

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.

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