scholarly journals Seismic Signature of Transition Zone (Wolf Ramp) in Shale Deposits with Application of Frequency Analysis

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Anna Kwietniak ◽  
Tomasz Maćkowski ◽  
Kamil Cichostępski
Keyword(s):  
Reflection Coefficient ◽  
Transition Zone ◽  
Seismic Analysis ◽  
High Amplitude ◽  
Seismic Interpretation ◽  
Seismic Survey ◽  
Baltic Basin ◽  
Linear Change ◽  
Seismic Section ◽  
Reservoir Volume

The concept of a transition zone, known as Wolf ramp, was incorporated into the seismic interpretation of a 3D seismic survey situated within the Baltic Basin (Northern Poland). Within the survey area, there exists one formation, the Pasłęk Formation, (Lower Silurian—Llandovery), that exhibits a linear change of velocity. This characteristic—linear change of velocity—causes a reflection coefficient (i.e., seismic amplitude) produced at such a boundary to be frequency dependent. The Pasłęk Formation was considered to be a potential shale gas reservoir and it was necessary to determine its structural position and thickness. The formation is challenging for robust seismic interpretation on the migrated seismic section—it does not manifest a stable reflection coefficient, and the amplitude contrast associated with the borders of the formation is low. There is no impedance contrast that would produce a reflection of high amplitude at the top or base of the formation which excludes determination of the formation thickness, hence the estimation of reservoir volume. Within a 3D dataset, there exists only one well with complete logs that were used for the analysis. The Pasłęk Formation is a flat-lying layer that continues itself far beyond the 3D survey. It is present in wells in the vicinity of the study area. These wells lay within other 3D or 2D datasets, but the quality of the seismic is poor, and similar seismic analysis is not possible. Nevertheless, these wells were incorporated in the research to reason about the possible link between the existence of transition zone and mineral content. The method used for recognition of transition zone is spectral decomposition and spectral analyses. The integrated studies enabled us to find a link between the Wolf ramp and mudstone-claystone interval of the Silurian age and give a new example of a transition zone which is present in shale plays. The transition zone concept might be applied for shale plays identification and analysis.

Using relative geologic time to constrain CNN-based seismic interpretation and property estimation

Geophysics ◽  
2021 ◽  
pp. 1-44
Author(s):  
Aria Abubakar ◽  
Haibin Di ◽  
Zhun Li
Keyword(s):  
Large Scale ◽  
Three Dimensional ◽  
Seismic Interpretation ◽  
Seismic Survey ◽  
Geologic Time ◽  
Seismic Amplitude ◽  
Property Estimation ◽  
Constrained Learning ◽  
Seismic Amplitudes ◽  
Multiplicative Regularization

Three-dimensional seismic interpretation and property estimation is essential to subsurface mapping and characterization, in which machine learning, particularly supervised convolutional neural network (CNN) has been extensively implemented for improved efficiency and accuracy in the past years. In most seismic applications, however, the amount of available expert annotations is often limited, which raises the risk of overfitting a CNN particularly when only seismic amplitudes are used for learning. In such a case, the trained CNN would have poor generalization capability, causing the interpretation and property results of obvious artifacts, limited lateral consistency and thus restricted application to following interpretation/modeling procedures. This study proposes addressing such an issue by using relative geologic time (RGT), which explicitly preserves the large-scale continuity of seismic patterns, to constrain a seismic interpretation and/or property estimation CNN. Such constrained learning is enforced in twofold: (1) from the perspective of input, the RGT is used as an additional feature channel besides seismic amplitude; and more innovatively (2) the CNN has two output branches, with one for matching the target interpretation or properties and the other for reconstructing the RGT. In addition is the use of multiplicative regularization to facilitate the simultaneous minimization of the target-matching loss and the RGT-reconstruction loss. The performance of such an RGT-constrained CNN is validated by two examples, including facies identification in the Parihaka dataset and property estimation in the F3 Netherlands dataset. Compared to those purely from seismic amplitudes, both the facies and property predictions with using the proposed RGT constraint demonstrate significantly reduced artifacts and improved lateral consistency throughout a seismic survey.

Exploring for stratigraphic traps in the Patchawarra Formation, Cooper Basin: an integrated seismic methodology

2018 ◽  
Vol 58 (2) ◽  
pp. 779
Author(s):  
Alexandra Bennett
Keyword(s):  
Complex Geometry ◽  
Imaging Techniques ◽  
South Australia ◽  
Seismic Interpretation ◽  
Seismic Survey ◽  
3D Seismic ◽  
Seismic Resolution ◽  
Seismic Reflectivity ◽  
Seismic Area ◽  
Cooper Basin

The Patchawarra Formation is characterised by Permian aged fluvial sediments. The conventional hydrocarbon play lies within fluvial sandstones, attributed to point bar deposits and splays, that are typically overlain by floodbank deposits of shales, mudstones and coals. The nature of the deposition of these sands has resulted in the discovery of stratigraphic traps across the Western Flank of the Cooper Basin, South Australia. Various seismic techniques are being used to search for and identify these traps. High seismic reflectivity of the coals with the low reflectivity of the relatively thin sands, often below seismic resolution, masks a reservoir response. These factors, combined with complex geometry of these reservoirs, prove a difficult play to image and interpret. Standard seismic interpretation has proven challenging when attempting to map fluvial sands. Active project examples within a 196 km2 3D seismic survey detail an evolving seismic interpretation methodology, which is being used to improve the delineation of potential stratigraphic traps. This involves an integration of seismic processing, package mapping, seismic attributes and imaging techniques. The integrated seismic interpretation methodology has proven to be a successful approach in the discovery of stratigraphic and structural-stratigraphic combination traps in parts of the Cooper Basin and is being used to extend the play northwards into the 3D seismic area discussed.

Shallow seismic reflection study of a glaciated valley

Geophysics ◽  
1998 ◽  
Vol 63 (4) ◽  
pp. 1395-1407 ◽  
Author(s):  
Frank Büker ◽  
Alan G. Green ◽  
Heinrich Horstmeyer
Keyword(s):  
Seismic Reflection ◽  
High Amplitude ◽  
Data Sets ◽  
Seismic Section ◽  
Data Set ◽  
Seismic Reflection Data ◽  
Northern Switzerland ◽  
Reflection Data ◽  
Shallow Seismic ◽  
Glaciated Valley

Shallow seismic reflection data were recorded along two long (>1.6 km) intersecting profiles in the glaciated Suhre Valley of northern Switzerland. Appropriate choice of source and receiver parameters resulted in a high‐fold (36–48) data set with common midpoints every 1.25 m. As for many shallow seismic reflection data sets, upper portions of the shot gathers were contaminated with high‐amplitude, source‐generated noise (e.g., direct, refracted, guided, surface, and airwaves). Spectral balancing was effective in significantly increasing the strength of the reflected signals relative to the source‐generated noise, and application of carefully selected top mutes ensured guided phases were not misprocessed and misinterpreted as reflections. Resultant processed sections were characterized by distributions of distinct seismic reflection patterns or facies that were bounded by quasi‐continuous reflection zones. The uppermost reflection zone at 20 to 50 ms (∼15 to ∼40 m depth) originated from a boundary between glaciolacustrine clays/silts and underlying glacial sands/gravels (till) deposits. Of particular importance was the discovery that the deepest part of the valley floor appeared on the seismic section at traveltimes >180 ms (∼200 m), approximately twice as deep as expected. Constrained by information from boreholes adjacent to the profiles, the various seismic units were interpreted in terms of unconsolidated glacial, glaciofluvial, and glaciolacustrine sediments deposited during two principal phases of glaciation (Riss at >100 000 and Würm at ∼18 000 years before present).

Frequency-dependent seismic analysis: Data processing, modeling, and interpretation

2019 ◽  
Vol 38 (7) ◽  
pp. 556-557
Author(s):  
Yi Shen ◽  
Kui Bao ◽  
Doug Foster ◽  
Dhananjay Kumar ◽  
Kris Innanen ◽  
...  
Keyword(s):  
Model Building ◽  
Seismic Analysis ◽  
Rock Physics ◽  
Analysis Data ◽  
Seismic Interpretation ◽  
Seismic Attenuation ◽  
Frequency Dependent ◽  
University Of Texas ◽  
Q Model ◽  
Physics Modeling

A one-day postconvention workshop held during the 2018 SEG Annual Meeting in Anaheim, California, focused on seismic attenuation model building and compensation through imaging in the morning and on frequency-dependent seismic interpretation and rock physics in the afternoon. The workshop was organized by Dhananjay Kumar (BP), Yi Shen (Shell), Kui Bao (Shell), Mark Chapman (University of Edinburgh), Doug Foster (The University of Texas at Austin), Wenyi Hu (Advanced Geophysical Tech Inc.), and Tieyuan Zhu (Pennsylvania State University). The main topics discussed were: attenuation and Q model building using seismic, vertical seismic profiling, well-log and core data, seismic attenuation compensation, rock-physics modeling, seismic modeling, and frequency-dependent seismic interpretation.

THE YELLOWTAIL OIL DISCOVERY

1983 ◽  
Vol 23 (1) ◽  
pp. 170
Author(s):  
A. R. Limbert ◽  
P. N. Glenton ◽  
J. Volaric
Keyword(s):  
Oil Recovery ◽  
Seismic Data ◽  
Joint Venture ◽  
Seismic Survey ◽  
3D Seismic ◽  
Well Control ◽  
Reservoir Volume ◽  
3D Data ◽  
Small Feature ◽  
Gippsland Basin

The Esso/Hematite Yellowtall oil discovery is located about 80 km offshore in the Gippsland Basin. It is a small accumulation situated between the Mackerel and Kingfish oilfields. The oil is contained in Paleocene Latrobe Group sandstones, and sealed by the calcareous shales and siltstones of the Oligocene to Miocene Lakes Entrance Formation. Structural movement and erosion have combined to produce a low relief closure on the unconformity surface at the top of the Latrobe Group.The discovery well, Yellowtail-1, was the culmination of an exploration programme initiated during the early 1970's. The early work involved the recording and interpretation of conventional seismic data and resulted in the drilling of Opah- 1 in 1977. Opah-1 failed to intersect reservoir- quality sediments within the interpreted limits of closure although oil indications were encountered in a non-net interval immediately below the top of the Latrobe Group. In 1980 the South Mackerel 3D seismic survey was recorded. The interpretation of these 3D data in conjunction with the existing well control resulted in the drilling of Yellowtail-1 and subsequently led to the drilling of Yellowtail-2.In spite of the intensive exploration to which this small feature has been subjected, the potential for its development remains uncertain. Technical factors which affect the viability of a Yellowtail development are:The low relief of the closure makes the reservoir volume highly sensitive to depth conversion of the seismic data.The complicated velocity field makes precise depth conversion difficult.The thin oil column reduces oil recovery efficiency.The detailed pattern of erosion at the top of the Latrobe Group may be beyond the resolution capability of 3D seismic data.The 3D seismic data may not be capable of defining the distribution of the non-net intervals within the trap.The large anticlinal closures and topographic highs in the Gippsland Basin have been drilled, and the prospects that remain are generally small or high risk. Such exploration demands higher technology in the exploration stage and more wells to define the discoveries, and has no guarantee of success. The Yellowtail discovery is an illustration of one such prospect that the Esso/Hematite joint venture is evaluating.

Using machine learning as an aid to seismic geomorphology, which attributes are the best input?

2019 ◽  
Vol 7 (3) ◽  
pp. SE1-SE18 ◽  
Author(s):  
Lennon Infante-Paez ◽  
Kurt J. Marfurt
Keyword(s):  
Machine Learning ◽  
Volcanic Rocks ◽  
High Amplitude ◽  
Machine Learning Algorithms ◽  
Pyroclastic Flows ◽  
Seismic Survey ◽  
Self Organizing Maps ◽  
Target Pattern ◽  
Seismic Geomorphology ◽  
Amplitude Data

Volcanic rocks with intermediate magma composition indicate distinctive patterns in seismic amplitude data. Depending on the processes by which they were extruded to the surface, these patterns may be chaotic, moderate-amplitude reflectors (indicative of pyroclastic flows) or continuous high-amplitude reflectors (indicative of lava flows). We have identified appropriate seismic attributes that highlight the characteristics of such patterns and use them as input to self-organizing maps to isolate these volcanic facies from their clastic counterpart. Our analysis indicates that such clustering is possible when the patterns are approximately self-similar, such that the appearance of objects does not change at different scales of observation. We adopt a workflow that can help interpreters to decide what methods and what attributes to use as an input for machine learning algorithms, depending on the nature of the target pattern of interest, and we apply it to the Kora 3D seismic survey acquired offshore in the Taranaki Basin, New Zealand. The resulting clusters are then interpreted using the limited well control and principles of seismic geomorphology.

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