Aleutian Trench, Shumagin Segment, Seismic Section 104

1986 ◽  
pp. 14-19 ◽  
Author(s):  
Terry R. Bruns ◽  
Roland von Huene
Keyword(s):  
Seismic Section

scholarly journals Phase-array decomposition of a seismic section

1997 ◽  
Vol 128 (1) ◽  
pp. 241-252
Author(s):  
Roland Roberts ◽  
Ari Tryggvason
Keyword(s):  
Phase Array ◽  
Seismic Section

Prediction of Petrophysical Properties from Seismic Inversion and Neural Network: A case study

2021 ◽  
Author(s):  
Siddharth Garia ◽  
Arnab Kumar Pal ◽  
Karangat Ravi ◽  
Archana M Nair
Keyword(s):  
Neural Network ◽  
Bulk Density ◽  
Low Frequency ◽  
Seismic Inversion ◽  
Well Log ◽  
Petrophysical Properties ◽  
Seismic Section ◽  
Frequency Model ◽  
Seismic Reflection Data ◽  
Reflection Data

<p>Seismic inversion method is widely used to characterize reservoirs and detect zones of interest, i.e., hydrocarbon-bearing zone in the subsurface by transforming seismic reflection data into quantitative subsurface rock properties. The primary aim of seismic inversion is to transform the 3D seismic section/cube into an acoustic impedance (AI) cube. The integration of this elastic attribute, i.e., AI cube with well log data, can thereafter help to establish correlations between AI and different petrophysical properties. The seismic inversion algorithm interpolates and spatially populates data/parameters of wells to the entire seismic section/cube based on the well log information. The case study presented here uses machine learning-neural network based algorithm to extract the different petrophysical properties such as porosity and bulk density from the seismic data of the Upper Assam basin, India. We analyzed three different stratigraphic  units that are established to be producing zones in this basin.</p><p> AI model is generated from the seismic reflection data with the help of colored inversion operator. Subsequently, low-frequency model is generated from the impedance data extracted from the well log information. To compensate for the band limited nature of the seismic data, this low-frequency model is added to the existing acoustic model. Thereafter, a feed-forward neural network (NN) is trained with AI as input and porosity/bulk density as target, validated with NN generated porosity/bulk density with actual porosity/bulk density from well log data. The trained network is thus tested over the entire region of interest to populate these petrophysical properties.</p><p>Three seismic zones were identified from the seismic section ranging from 681 to 1333 ms, 1528 to 1575 ms and 1771 to 1814 ms. The range of AI, porosity and bulk density were observed to be 1738 to 6000 (g/cc) * (m/s), 26 to 38% and 1.95 to 2.46 g/cc respectively. Studies conducted by researchers in the same basin yielded porosity results in the range of 10-36%. The changes in acoustic impedance, porosity and bulk density may be attributed to the changes in lithology. NN method was prioritized over other traditional statistical methods due to its ability to model any arbitrary dependency (non-linear relationships between input and target values) and also overfitting can be avoided. Hence, the workflow presented here provides an estimation of reservoir properties and is considered useful in predicting petrophysical properties for reservoir characterization, thus helping to estimate reservoir productivity.</p>

Kirchhoff elastic wave migration for the case of noncoincident source and receiver

Geophysics ◽  
1984 ◽  
Vol 49 (8) ◽  
pp. 1223-1238 ◽  
Author(s):  
John T. Kuo ◽  
Ting‐fan Dai
Keyword(s):  
Elastic Wave ◽  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Horizontal Layer ◽  
P Wave ◽  
Seismic Section ◽  
S Waves ◽  
Surface Data ◽  
Marine Seismic ◽  
Wave Migration

In taking into account both compressional (P) and shear (S) waves, more geologic information can likely be extracted from the seismic data. The presence of shear and converted shear waves in both land and marine seismic data recordings calls for the development of elastic wave‐migration methods. The migration method presently developed consists of simultaneous migration of P- and S-waves for offset seismic data based on the Kirchhoff‐Helmholtz type integrals for elastic waves. A new principle of simultaneously migrating both P- and S-waves is introduced. The present method, named the Kirchhoff elastic wave migration, has been tested using the 2-D synthetic surface data calculated from several elastic models of a dipping layer (including a horizontal layer), a composite dipping and horizontal layer, and two layers over a half‐space. The results of these tests not only assure the feasibility of this migration scheme, but also demonstrate that enhanced images in the migrated sections are well formed. Moreover, the signal‐to‐noise ratio increases in the migrated seismic section by this elastic wave migration, as compared with that using the Kirchhoff acoustic (P-) wave migration alone. This migration scheme has about the same order of sensitivity of migration velocity variations, if [Formula: see text] and [Formula: see text] vary concordantly, to the recovery of the reflector as that of the Kirchhoff acoustic (P-) wave migration. In addition, the sensitivity of image quality to the perturbation of [Formula: see text] has also been tested by varying either [Formula: see text] or [Formula: see text]. For varying [Formula: see text] (with [Formula: see text] fixed), the migrated images are virtually unaffected on the [Formula: see text] depth section while they are affected on the [Formula: see text] depth section. For varying [Formula: see text] (with [Formula: see text] fixed), the migrated images are affected on both the [Formula: see text] and [Formula: see text] depth sections.

scholarly journals Increasing the quality of seismic interpretation

2016 ◽  
Vol 4 (3) ◽  
pp. T395-T402 ◽  
Author(s):  
Euan J. Macrae ◽  
Clare E. Bond ◽  
Zoe K. Shipton ◽  
Rebecca J. Lunn
Keyword(s):  
Controlled Trial ◽  
Causal Link ◽  
Environmental Risks ◽  
Influential Factor ◽  
Data Sets ◽  
Seismic Section ◽  
Randomized Controlled ◽  
First Time ◽  
Geologic Data

Geologic models are based on the interpretation of spatially sparse and limited resolution data sets. Nonunique interpretations often exist, resulting in commercial, safety, and environmental risks. We surveyed 444 experienced geoscientists to assess the validity of their interpretations of a seismic section for which multiple concepts honor the data. The most statistically influential factor in improving interpretation was writing about geologic time. A randomized controlled trial identified for the first time a significant causal link between being explicitly requested to describe the temporal geologic evolution of an interpretation and increased interpretation quality. These results have important implications for interpreting geologic data and communicating uncertainty in models.

scholarly journals Influence of geophysical judgement and software parameters on interpretation of seismic section

2016 ◽  
Author(s):  
V.R. Balasubramaniam ◽  
P.C. Jha ◽  
Babu B Butchi ◽  
S. Nelliat ◽  
Y.V. Sivaram ◽  
...  
Keyword(s):  
Seismic Section

scholarly journals ATENUASI WATER-BOTTOM MULTIPLE DENGAN METODE TRANSFORMASI PARABOLIC RADON

2016 ◽  
Vol 12 (3) ◽  
pp. 145
Author(s):  
Subarsyah Subarsyah ◽  
Tumpal Benhard Nainggolan
Keyword(s):  
Radon Transform ◽  
Seismic Data ◽  
Wide Distribution ◽  
Seismic Section ◽  
Optimal Separation ◽  
Multiple Attenuation ◽  
Parabolic Radon Transform ◽  
Water Bottom

Interferensi water-bottom multipel terhadap reflektor primer menimbulkan efek bersifat destruktif yang menyebabkan penampang seismik menjadi tidak tepat akibat kehadiran reflektor semu. Teknik demultiple perlu diaplikasikan untuk mengatenuasi multipel. Transformasi parabolic radon merupakan teknik atenuasi multipel dengan metode pemisahan dalam domain radon. Multipel sering teridentifikasi pada penampang seismik. Untuk memperbaiki penampang seismik akan dilakukan dengan metode transformasi parabolic radon. Penerapan metode ini mengakibatkan reflektor multipel melemah dan tereduksi setelah dilakukan muting dalam domain radon terhadap zona multipel. Beberapa reflektor primer juga ikut melemah akibat pemisahan dalam domain radon yang kurang optimal, pemisahan akan optimal membutuhkan distribusi offset yang lebar. Kata kunci: Parabolic radon, multipel, atenuasi Water-bottom mutiple interference often destructively interfere with primary reflection that led to incorrect seismic section due to presence apparent reflector. Demultiple techniques need to be applied to attenuate the multiple. Parabolic Radon transform is demultiple attenuation technique that separate multiple and primary in radon domain. Water-bottom mutiple ussualy appear and easly identified on seismic data, parabolic radon transform applied to improve the seismic section. Application of this method to data showing multiple reflectors weakened and reduced after muting multiple zones in the radon domain. Some of the primary reflector also weakened due to bad separation in radon domain, optimal separation will require a wide distribution of offsets. Keywords: Parabolic radon, multiple, attenuation

scholarly journals Stratigraphic-Seismic Section Correlations and Implications to Bengal Fan History

1974 ◽  
Author(s):  
D.G. Moore ◽  
J.R. Curray ◽  
R.W. Raitt ◽  
F.J. Emmel
Keyword(s):  
Seismic Section ◽  
Bengal Fan

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).

Picking noisy refraction data using semblance supplemented by a Monte Carlo procedure and spectral balancing

1987 ◽  
Vol 77 (3) ◽  
pp. 942-957
Author(s):  
C. A. Zelt ◽  
J. J. Drew ◽  
M. J. Yedlin ◽  
R. M. Ellis
Keyword(s):  
Monte Carlo ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
Time Shift ◽  
Head Wave ◽  
Signal To Noise ◽  
Seismic Section ◽  
Monte Carlo Procedure ◽  
Noise Ratio ◽  
Refraction Data

Abstract In crustal refraction experiments, the crucial deeply refracted and head wave arrivals often have a low signal-to-noise ratio. A method to aid in the picking of noisy refraction data is presented which is applicable to any branch of a seismic section whose waveform is approximately invariant throughout the branch. The technique exploits the spatial correlation of arrivals and is based on the lateral coherency which results if the refracted arrivals are aligned by applying appropriate time shifts to each trace of the branch. The alignment of arrivals occurs iteratively and is accomplished through a cross-correlation of each trace with the stack of the section of the previous iteration. The iteration yielding the section with the highest degree of lateral coherency (semblance) is used to extract the travel-time pick of each trace. The pick, plus a possible d.c. component, is the negative of the time shift required to achieve arrival alignment. Two modifications can improve the performance of the picking routine. To prevent a cycle skipping problem, a Monte Carlo technique is implemented in which the cross-correlation function is transformed into a probability distribution so that the lag corresponding to the maximum cross-correlation is most probably selected. Second, to increase the coherency of the arrivals, a spectral balancing technique is applied in either the time or frequency domain. The picking routine is applied to both a synthetic and real data example, and the results suggest that the routine can be applied successfully to data with a signal-to-noise ratio as low as one. Also, the Monte Carlo procedure together with spectral balancing increases the final semblance over that obtained with the unmodified method.

Assessment of gas hydrate using pre-stack seismic inversion in Mahanadi Basin, offshore eastern India

2021 ◽  
pp. 1-42
Author(s):  
Maheswar Ojha ◽  
Ranjana Ghosh
Keyword(s):  
Gas Hydrate ◽  
Rock Physics ◽  
Type Equation ◽  
Seismic Inversion ◽  
Log Analysis ◽  
Well Log ◽  
Seismic Section ◽  
Bottom Simulating Reflector ◽  
Hydrate Saturation ◽  
Well Log Analysis

The Indian National Gas Hydrate Program Expedition-01 in 2006 has discovered gas hydrate in Mahanadi offshore basin along the eastern Indian margin. However, well log analysis, pressure core measurements and Infra-Red (IR) anomalies reveal that gas hydrates are distributed as disseminated within the fine-grained sediment, unlike massive gas hydrate deposits in the Krishna-Godavari basin. 2D multi-channel seismic section, which crosses the Holes NGHP-01-9A and 19B located at about 24 km apart shows a continuous bottom-simulating reflector (BSR) along it. We aim to investigate the prospect of gas hydrate accumulation in this area by integrating well log analysis and seismic methods with rock physics modeling. First, we estimate gas hydrate saturation at these two Holes from the observed impedance using the three-phase Biot-type equation (TPBE). Then we establish a linear relationship between gas hydrate saturation and impedance contrast with respect to the water-saturated sediment. Using this established relation and impedance obtained from pre-stack inversion of seismic data, we produce a 2D gas hydrate-distribution image over the entire seismic section. Gas hydrate saturation estimated from resistivity and sonic data at well locations varies within 0-15%, which agrees well with the available pressure core measurements at Hole 19. However, the 2D map of gas hydrate distribution obtained from our method shows maximum gas hydrate saturation is about 40% just above the BSR between the CDP (common depth point) 1450 and 2850. The presence of gas-charged sediments below the BSR is one of the reasons for the strong BSR observed in the seismic section, which is depicted as low impedance in the inverted impedance section. Closed sedimentary structures above the BSR are probably obstructing the movements of free-gas upslope, for which we do not see the presence of gas hydrate throughout the seismic section above the BSR.

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