Seismic‐attribute analysis utilizing multiazimuth seismic data in the offshore Nile Delta — A case study

2007 ◽  
Author(s):  
Robert Marten ◽  
Walter Rietveld ◽  
Mark Benson ◽  
Alaa Khodeir ◽  
James Keggin ◽  
...  
Keyword(s):  
Seismic Data ◽  
Nile Delta ◽  
Seismic Attribute ◽  
Attribute Analysis

Delineation of reservoir channels by different seismic attributes and geobody extractions for robust volumetric estimation, Saffron Field, offshore Nile Delta, Egypt

2021 ◽  
Vol 40 (7) ◽  
pp. 484-493
Author(s):  
Doha Monier ◽  
Azza El Rawy ◽  
Abdullah Mahmoud
Keyword(s):  
Seismic Data ◽  
Nile Delta ◽  
Three Dimensional ◽  
Dynamic Test ◽  
Data Interpretation ◽  
Seismic Attributes ◽  
Reservoir Properties ◽  
Root Mean Square Amplitude ◽  
Seismic Attribute ◽  
Attribute Analysis

The Nile Delta Basin is a major gas province. Commercial gas discoveries there have been proven mainly in Pleistocene to Oligocene sediments, and most discoveries are within sandstone reservoirs. Three-dimensional seismic data acquired over the basin have helped greatly in imaging and visualization of stratigraphy and structure, leading to robust understanding of the subsurface. Channel fairways serve as potential reservoir units; hence, mapping channel surfaces and identifying and defining infill lithology is important. Predicting sand distribution and reservoir presence is one of the key tasks as well as one of the key uncertainties in exploration. Integrating state-of-the-art technologies, such as including 3D seismic reflection surveys, seismic attributes, and geobody extractions, can reduce this uncertainty through recognition and accurate mapping of channel features. In this study, seismic attribute analysis, frequency analysis through spectral decomposition (SD), geobodies, and seismic sections have been used to delineate shallow Plio-Pleistocene El Wastani Formation channel fairways within the Saffron Field, offshore Nile Delta, Egypt. This has led to providing more reliable inputs for calculation of volumetrics. Interpretation of the stacked-channels complex through different seismic attributes helped to discriminate between sand-filled and shale-filled channels and in understanding their geometries. Results include more confident delineation of four distinct low-sinuosity channelized features. Petrophysical evaluation conducted on five wells penetrating Saffron reservoirs included electric logs and modular dynamic test data interpretation. The calculated average reservoir properties were used in different volumetric calculation cases. Different approaches were applied to delineate channel geometries that were later used in performing different volumetric cases. These approaches included defining channels from root-mean-square amplitude extractions, SD color-blended frequencies, and geobodies, all calculated from prestack seismic data. The different volumetric cases performed were compared against the latest field volume estimates proven after several years of production in which an area-versus-depth input showed the closest calculated hydrocarbon volumes to the actual proven field volumes.

scholarly journals Seismic Identification of Unconventional Heterogenous Reservoirs Based on Depositional History—A Case Study of the Polish Carpathian Foredeep

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6036
Author(s):  
Anna Łaba-Biel ◽  
Anna Kwietniak ◽  
Andrzej Urbaniec
Keyword(s):  
Seismic Data ◽  
Spectral Decomposition ◽  
Sedimentary Basin ◽  
Seismic Stratigraphy ◽  
Seismic Attribute ◽  
Depositional History ◽  
Attribute Analysis ◽  
Carpathian Foredeep ◽  
The Subject

An integrated geological and geophysical approach is presented for the recognition of unconventional targets in the Miocene formations of the Carpathian Foredeep, southern Poland. The subject of the analysis is an unconventional reservoir built of interlayered packets of sandstone, mudstone and claystone, called a “heterogeneous sequence”. This type of sequence acts as both a reservoir and as source rock for hydrocarbons and it consists of layers of insignificant thickness, below the resolution of seismic data. The interpretation of such a sequence has rarely been based on seismic stratigraphy analysis; however, such an approach is proposed here. The subject of interpretation is high-quality seismic data of high resolution that enable detailed depositional analysis. The reconstruction of the depositional history was possible due to the analysis of flattened chronostratigraphic horizons (Wheeler diagram). The identification of depositional positions in a sedimentary basin was the first step for the indication of potential target areas. These areas were also subject to seismic attribute analysis (sweetness) and spectral decomposition. The seismic attribute results positively verified the previously proposed prospects. The results obtained demonstrate that the interpretation of the Miocene sediments in the Carpathian Foredeep should take into account the depositional history reconstruction and paleogeographical analysis.

Predict Channel Sand Body Distribution Characteristics of South Eighth District Based on RMS Amplitude Attributes & Frequency Division

2013 ◽  
Vol 734-737 ◽  
pp. 404-407 ◽  
Author(s):  
Yu Shuang Hu ◽  
Si Miao Zhu
Keyword(s):  
Seismic Data ◽  
Physical Property ◽  
Sedimentary Facies ◽  
Distribution Area ◽  
Frequency Division ◽  
Root Mean Square Amplitude ◽  
Seismic Attribute ◽  
Body Distribution ◽  
Attribute Analysis ◽  
Sand Body

A big tendency in oil industry is underestimating the heterogeneity of the reservoir and overestimating the connectivity, which results in overly optimistic estimates of the capacity. With the development of seismic attributes, we could pick up hidden reservoir lithology and physical property information from the actual seismic data, strengthen seismic data application in actual work, to ensure the objectivity of the results. In this paper, the channel sand body distribution in south eighth district of oilfield Saertu is predicted through seismic data root-mean-square amplitude and frequency division to identify sand body boundaries, predict the distribution area channel sand body characteristics successfully, which consistent with the sedimentary facies distribution. The result proves that seismic attribute analysis has good practicability in channel sand body prediction and sedimentary facies description.

THE INTEGRATION OF MODERN TECHNOLOGY IN GIPPSLAND'S CENTRAL FIELDS STUDY

1994 ◽  
Vol 34 (1) ◽  
pp. 513
Author(s):  
P.V.Hinton P.V.Hinton ◽  
M.G.Cousins ◽  
P.E.Symes
Keyword(s):  
Seismic Data ◽  
Field Performance ◽  
Simulation Models ◽  
Modern Technology ◽  
Depositional Environments ◽  
Seismic Attribute ◽  
Sequence Stratigraphic ◽  
Multidisciplinary Study ◽  
Attribute Analysis ◽  
Definition Of

The central fields area of the Gippsland Basin, Australia, includes the Halibut, Cobia, Fortescue, and Mackerel oil fields. These large fields are mature with about 80% of the reserves produced. During 1991 and 1992 a multidisciplinary study, integrating the latest technology, was completed to help optimise the depletion of the remaining significant reserves.A grid of 4500 km of high resolution 3D seismic data covering 191 square kilometres allowed the identification of subtle structural traps as well as better definition of sandstone truncation edges which represent the ultimate drainage points. In addition, the latest techniques in seismic attribute analysis provided insight into depositional environments, seal potential and facies distribution. Sequence stratigraphic concepts were used in combination with seismic data to build complex multi million cell 3D geological models. Reservoir simulation models were then constructed to history match past production and to predict future field performance. Facility studies were also undertaken to optimise depletion strategies.The Central Fields Depletion Study has resulted in recommendations to further develop the fields with about 80 work-overs, 50 infill wells, reduction in separator pressures, and gas lift and water handling facility upgrades. These activities are expected to increase ultimate reserves and production. Some of the recommendations have been implemented with initial results of additional drilling on Mackerel increasing platform production from 22,000 BOPD to over 50,000 BOPD. An ongoing program of additional drilling from the four platforms is expected to continue for several years.

Application of seismic attribute analysis and subsurface structure interpretation for hydrocarbon prospects: A case study of Indus Basin, Pakistan

2020 ◽  
Author(s):  
Muhammad Bilal Malik ◽  
Matloob Hussain ◽  
Armghan Faisal Meraj ◽  
Sher Afgan ◽  
Pal Washa Shahzad Rathore
Keyword(s):  
Indus Basin ◽  
Subsurface Structure ◽  
Seismic Attribute ◽  
Attribute Analysis

Accelerating seismic fault and stratigraphy interpretation with deep CNNs: A case study of the Taranaki Basin, New Zealand

2020 ◽  
Vol 39 (10) ◽  
pp. 727-733
Author(s):  
Haibin Di ◽  
Leigh Truelove ◽  
Cen Li ◽  
Aria Abubakar
Keyword(s):  
New Zealand ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Seismic Survey ◽  
Deep Convolutional Neural Networks ◽  
Seismic Attribute ◽  
Data Set ◽  
Seismic Fault ◽  
Attribute Analysis ◽  
Specific Implementation

Accurate mapping of structural faults and stratigraphic sequences is essential to the success of subsurface interpretation, geologic modeling, reservoir characterization, stress history analysis, and resource recovery estimation. In the past decades, manual interpretation assisted by computational tools — i.e., seismic attribute analysis — has been commonly used to deliver the most reliable seismic interpretation. Because of the dramatic increase in seismic data size, the efficiency of this process is challenged. The process has also become overly time-intensive and subject to bias from seismic interpreters. In this study, we implement deep convolutional neural networks (CNNs) for automating the interpretation of faults and stratigraphies on the Opunake-3D seismic data set over the Taranaki Basin of New Zealand. In general, both the fault and stratigraphy interpretation are formulated as problems of image segmentation, and each workflow integrates two deep CNNs. Their specific implementation varies in the following three aspects. First, the fault detection is binary, whereas the stratigraphy interpretation targets multiple classes depending on the sequences of interest to seismic interpreters. Second, while the fault CNN utilizes only the seismic amplitude for its learning, the stratigraphy CNN additionally utilizes the fault probability to serve as a structural constraint on the near-fault zones. Third and more innovatively, for enhancing the lateral consistency and reducing artifacts of machine prediction, the fault workflow incorporates a component of horizontal fault grouping, while the stratigraphy workflow incorporates a component of feature self-learning of a seismic data set. With seven of 765 inlines and 23 of 2233 crosslines manually annotated, which is only about 1% of the available seismic data, the fault and four sequences are well interpreted throughout the entire seismic survey. The results not only match the seismic images, but more importantly they support the graben structure as documented in the Taranaki Basin.

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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