VIBROSEIS DOWN THE HOLE

1983 ◽  
Vol 23 (1) ◽  
pp. 203
Author(s):  
J. T. Frazer
Keyword(s):  
Seismic Data ◽  
Seismic Source ◽  
Seismic Signal ◽  
Structure Mapping ◽  
Time Duration ◽  
Seismic Section ◽  
Reflection Seismic ◽  
The Past ◽  
Field Estimation ◽  
Seismic Reflections

A variety of problems associated with the Vibroseis® source have been encountered over the past few years which have presented difficulties in tieing surveys using different control systems and in depth mapping.Accurate depth structure mapping and field estimation from seismic data requires good correlation of seismic reflections with stratigraphic boundaries. The information required, a known seismic signal and vertical rock velocities can only be obtained from measurements down the hole.Seismic time to depth correlation can be obtained from an integrated sonic velocity curve tied to conventional well shoot data only if the source is the same as that used for the reflection seismic data or the relation between the well shoot and seismic source is known. It has been apparent for some time that the signal from the Vibroseis source has not been adequately defined from surface measurements.A number of parameters must be monitored to ensure that the signal transmitted during a Vibroseis sweep is properly calibrated. The synchronisation of phase, time duration of the sweep, sweep bandwidth, vibrator drive levels and the phase relation of the pilot sweep to the signal transmitted from the baseplate, contribute to determine the character of the signal seen on a seismic section.®Trademark of Conoco, Inc.

scholarly journals Applicataion of ormsby wavelet for generation of synthetic seismic signals

2018 ◽  
Vol 7 (2.7) ◽  
pp. 794
Author(s):  
E Sai Sumanth ◽  
V Joseph ◽  
Dr K S Ramesh ◽  
Dr S Koteswara Rao
Keyword(s):  
Wavelet Transform ◽  
Seismic Data ◽  
Wavelet Transforms ◽  
Seismic Signal ◽  
Core Structure ◽  
Seismic Signals ◽  
Seismic Reflections ◽  
Input Wave

Investigation of signals reflected from earth’s surface and its crust helps in understanding its core structure. Wavelet transforms is one of the sophisticated tools for analyzing the seismic reflections. In the present work a synthetic seismic signal contaminated with noise is synthesized  and analyzed using Ormsby wavelet[1]. The wavelet transform has efficiently extracted the spectra of the synthetic seismic signal as it smoothens the noise present in the data and upgrades the flag quality of the seismic data due to termers. Ormsby wavelet gives the most redefined spectrum of the input wave so it could be used for the analysis of the seismic reflections. 

scholarly journals A method of combining coherence-constrained sparse coding and dictionary learning for denoising

Geophysics ◽  
2017 ◽  
Vol 82 (3) ◽  
pp. V137-V148 ◽  
Author(s):  
Pierre Turquais ◽  
Endrias G. Asgedom ◽  
Walter Söllner
Keyword(s):  
Dictionary Learning ◽  
Seismic Data ◽  
Random Noise ◽  
A Priori ◽  
Seismic Signal ◽  
Noise Variance ◽  
A Priori Information ◽  
Seismic Section ◽  
Learned Dictionary ◽  
Priori Information

We have addressed the seismic data denoising problem, in which the noise is random and has an unknown spatiotemporally varying variance. In seismic data processing, random noise is often attenuated using transform-based methods. The success of these methods in denoising depends on the ability of the transform to efficiently describe the signal features in the data. Fixed transforms (e.g., wavelets, curvelets) do not adapt to the data and might fail to efficiently describe complex morphologies in the seismic data. Alternatively, dictionary learning methods adapt to the local morphology of the data and provide state-of-the-art denoising results. However, conventional denoising by dictionary learning requires a priori information on the noise variance, and it encounters difficulties when applied for denoising seismic data in which the noise variance is varying in space or time. We have developed a coherence-constrained dictionary learning (CDL) method for denoising that does not require any a priori information related to the signal or noise. To denoise a given window of a seismic section using CDL, overlapping small 2D patches are extracted and a dictionary of patch-sized signals is trained to learn the elementary features embedded in the seismic signal. For each patch, using the learned dictionary, a sparse optimization problem is solved, and a sparse approximation of the patch is computed to attenuate the random noise. Unlike conventional dictionary learning, the sparsity of the approximation is constrained based on coherence such that it does not need a priori noise variance or signal sparsity information and is still optimal to filter out Gaussian random noise. The denoising performance of the CDL method is validated using synthetic and field data examples, and it is compared with the K-SVD and FX-Decon denoising. We found that CDL gives better denoising results than K-SVD and FX-Decon for removing noise when the variance varies in space or time.

scholarly journals Reflection seismic studies over the end-glacial Burträsk fault, Skellefteå, Sweden

2010 ◽  
Vol 2 (2) ◽  
pp. 307-329 ◽  
Author(s):  
C. Juhlin ◽  
B. Lund
Keyword(s):  
Fracture Zone ◽  
Seismic Data ◽  
Mafic Rock ◽  
Seismic Profile ◽  
Large Displacements ◽  
Fault Geometry ◽  
Seismic Section ◽  
Glacial Ice ◽  
Crustal Rocks ◽  
Reflection Seismic

Abstract. Reflection seismic data were acquired along a ca. 22 km long profile over the end-glacial Burträsk Fault with a nominal receiver and source spacing of 20 m. A steeply dipping reflection can be correlated to the Burträsk Fault, indicating that the fault dips at about 55° to the southeast near the surface. The reflection from the fault is rather poorly imaged, probably due to a jump in the fault and the crookedness of the seismic profile in the vicinity of the fault. A more pronounced steeply dipping reflection is observed about 4 km southeast of the Burträsk Fault. Based on its correlation with a topographic low at the surface this reflection is interpreted to originate from a fracture zone. There are no signs of large displacements along this fault as the glacial ice receded, but it may be active today. Other reflections on the processed seismic section may originate from changes in lithological variations in the supra-crustal rocks or from intrusions of more mafic rock. Constraints on the fault geometry provided by the reflection seismic data will help determine what stresses were required to activate the fault when the major rupture along it occurred.

scholarly journals Reflection seismic studies over the end-glacial Burträsk fault, Skellefteå, Sweden

Solid Earth ◽  
2011 ◽  
Vol 2 (1) ◽  
pp. 9-16 ◽  
Author(s):  
C. Juhlin ◽  
B. Lund
Keyword(s):  
Seismic Data ◽  
Mafic Rock ◽  
Seismic Profile ◽  
Large Displacements ◽  
Fault Geometry ◽  
Seismic Section ◽  
Glacial Ice ◽  
Crustal Rocks ◽  
Reflection Seismic ◽  
Lateral Offset

Abstract. Reflection seismic data were acquired along a ca. 22 km long profile over the end-glacial Burträsk fault with a nominal receiver and source spacing of 20 m. A steeply dipping reflection can be correlated to the Burträsk fault, indicating that the fault dips at about 55° to the southeast near the surface. The reflection from the fault is rather poorly imaged, probably due to a lateral offset in the fault of about 1 km at this location and the crookedness of the seismic profile in the vicinity of the fault. A more pronounced steeply dipping reflection is observed about 4 km southeast of the Burträsk fault. Based on its correlation with a topographic low at the surface this reflection is interpreted to originate from a fracture zone. There are no signs of large displacements along this zone as the glacial ice receded, but earthquakes could be associated with it today. Other reflections on the processed seismic section may originate from changes in lithological variations in the supra-crustal rocks or from intrusions of more mafic rock. Constraints on the fault geometry provided by the reflection seismic data will help determine what stresses were required to activate the fault when the major rupture along it occurred ca. 9500 years ago.

scholarly journals Fault interpretation in seismic reflection data: an experiment analysing the impact of conceptual model anchoring and vertical exaggeration

Solid Earth ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 1651-1662 ◽  
Author(s):  
Juan Alcalde ◽  
Clare E. Bond ◽  
Gareth Johnson ◽  
Armelle Kloppenburg ◽  
Oriol Ferrer ◽  
...  
Keyword(s):  
Seismic Data ◽  
Seismic Reflection ◽  
Conceptual Models ◽  
Seismic Section ◽  
Seismic Reflection Data ◽  
Reflection Seismic ◽  
Reflection Data ◽  
Interpretation Process ◽  
Fault Interpretation ◽  
The Impact

Abstract. The use of conceptual models is essential in the interpretation of reflection seismic data. It allows interpreters to make geological sense of seismic data, which carries inherent uncertainty. However, conceptual models can create powerful anchors that prevent interpreters from reassessing and adapting their interpretations as part of the interpretation process, which can subsequently lead to flawed or erroneous outcomes. It is therefore critical to understand how conceptual models are generated and applied to reduce unwanted effects in interpretation results. Here we have tested how interpretation of vertically exaggerated seismic data influenced the creation and adoption of the conceptual models of 161 participants in a paper-based interpretation experiment. Participants were asked to interpret a series of faults and a horizon, offset by those faults, in a seismic section. The seismic section was randomly presented to the participants with different horizontal–vertical exaggeration (1:4 or 1:2). Statistical analysis of the results indicates that early anchoring to specific conceptual models had the most impact on interpretation outcome, with the degree of vertical exaggeration having a subdued influence. Three different conceptual models were adopted by participants, constrained by initial observations of the seismic data. Interpreted fault dip angles show no evidence of other constraints (e.g. from the application of accepted fault dip models). Our results provide evidence of biases in interpretation of uncertain geological and geophysical data, including the use of heuristics to form initial conceptual models and anchoring to these models, confirming the need for increased understanding and mitigation of these biases to improve interpretation outcomes.

Density‐based reflectivity in seismic exploration for coal in Alberta, Canada

Geophysics ◽  
1991 ◽  
Vol 56 (1) ◽  
pp. 139-141 ◽  
Author(s):  
D. C. Lawton ◽  
H. V. Lyatsky
Keyword(s):  
Seismic Data ◽  
Compressional Wave ◽  
Seismic Exploration ◽  
Coal Field ◽  
Compressional Wave Velocity ◽  
Coal Seams ◽  
Seismic Section ◽  
Reflection Seismic ◽  
Sonic Logs ◽  
Different Parts

At a coal field in central Alberta, Canada, the acoustic reflectivity of shallow coal seams was found to be dominated by the density contrast between coal and host bentonitic sediments. Sonic logs and a check‐shot survey showed that the compressional‐wave velocity is almost constant through the coal zone and the overlying sediments, and ranges in value between 2000 m/s and 2350 m/s over different parts of the coal field. The average coal density is [Formula: see text], whereas the density of the sediments is about [Formula: see text]. Results are illustrated using logs from a typical drillhole in the coal field. At this location, the time reflectivity sequence based on both the density and sonic logs is very similar to that obtained when the density log only is used, with a constant velocity assumed through the coal zone. At another drillhole location in the coal field, where reflection seismic data had been acquired, a synthetic seismogram generated from the density log closely matches the stacked seismic section.

scholarly journals SEISMIC SIGNAL ANALYSIS USING MINIMUM PHASE AND SINGULAR VALUE DECOMPOSITION METHODS. APPLICATION TO GROUNDROLL ATTENUATION

2019 ◽  
Vol 37 (2) ◽  
Author(s):  
Anderson Silva Santos ◽  
Milton José Porsani
Keyword(s):  
Singular Value Decomposition ◽  
Seismic Data ◽  
Seismic Signal ◽  
Singular Value ◽  
Frequency Noise ◽  
Minimum Phase ◽  
Phase Decomposition ◽  
Seismic Section ◽  
Reflectivity Function ◽  
Value Decomposition

ABSTRACT. A challenge in land seismic data processing is the coherent noise groundroll. This noise is related to the propagation of surface waves of the Rayleigh type, this undesired event has as characteristics: low frequencies, high amplitudes and strong dispersion, which masks the events of interest in the stacked seismic section. The seismic data from the Tacutu Basin, besides having a low signal-to-noise ratio, are also strongly contaminated by groundroll noise, which makes it a challenge to obtain stacked seismic section with high resolution of this sedimentary basin. The 1D and 2D frequency filters are widely used for groundroll attenuation, but these methods besides attenuating the noisy also eliminate part of the signal by rejecting part of the frequency band of the seismic signal. Therefore, we are introduce a new filter to groundroll attenuation that uses two powerful tools for decomposition of the seismic signal together, minimum phase decomposition and singular value decomposition. The proposed method aims to estimate the reflectivity function for each seismic trace and then perform a decomposition of this reflectivity function. Since the low frequency noise is confined in the first portion of the decomposed signal it is possible to make a separation between the noise and the signal. The filtering method was included in the 2D seismic processing flow chart of the Tacutu Basin. The results showed that the proposed method was capable of attenuate the groundroll noise and generated at the end a stacked seismic section with a good resolution. Keywords: minimum phase decomposition, singular value decomposition, groundroll attenuation.RESUMO. Um desafio no processamento de dados sísmicos terrestres é o ruído coerente groundroll. Este ruído está relacionado à propagação de ondas de superfície do tipo Rayleigh, este evento indesejado tem como características: baixas frequências, altas amplitudes e forte dispersão, o que mascara os eventos de interesse na seção sísmica empilhada. Os dados sísmicos da Bacia do Tacutu, além de apresentar uma baixa relação sinal-ruído, também estão fortemente contaminados pelo ruído do solo, o que dificulta a obtenção de seções sísmicas empilhadas com alta resolução desta bacia sedimentar. Os filtros de frequência 1D e 2D são amplamente utilizados para a atenuação do groundroll, mas esses métodos além de atenuar o ruído também eliminam parte do sinal rejeitando parte da banda de frequência do sinal sísmico. Portanto, estamos introduzindo um novo filtro para a atenuação de groundroll que usa duas ferramentas poderosas para a decomposição do sinal sísmico, decomposição em fase mínima e decomposição em valor singular. O método proposto tem como objetivo estimar a função de refletividade para cada traço sísmico e então realizar a decomposição dessa função refletividade. Uma vez que o ruído de baixa frequência é confinado na primeira porção do sinal decomposto, é possível fazer uma separação entre o ruído e o sinal. O método de filtragem foi incluído no fluxograma de processamento sísmico 2D da Bacia do Tacutu. Os resultados mostraram que o método proposto foi capaz de atenuar o ruído groundroll e gerar ao final uma seção sísmica empilhada com boa resolução.Palavras-chave: decomposição em fase mínima, decomposição em valores singulares, atenuação do groundroll.  

Seismic offset balancing

Geophysics ◽  
1994 ◽  
Vol 59 (1) ◽  
pp. 93-101 ◽  
Author(s):  
Christopher P. Ross ◽  
Paul L. Beale
Keyword(s):  
Seismic Data ◽  
Amplitude Variation With Offset ◽  
Reflection Seismic ◽  
Optimal Processing ◽  
Theoretical Predictions ◽  
Back Ground ◽  
Seismic Records ◽  
The Many ◽  
Seismic Reflections ◽  
The Relationship

The ability to successfully predict lithology and fluid content from reflection seismic records using AVO techniques is contingent upon accurate pre‐analysis conditioning of the seismic data. However, all too often, residual amplitude effects remain after the many offset‐dependent processing steps are completed. Residual amplitude effects often represent a significant error when compared to the amplitude variation with offset (AVO) response that we are attempting to quantify. We propose a model‐based, offset‐dependent amplitude balancing method that attempts to correct for these residuals and other errors due to sub‐optimal processing. Seismic offset balancing attempts to quantify the relationship between the offset response of back‐ground seismic reflections and corresponding theoretical predictions for average lithologic interfaces thought to cause these background reflections. It is assumed that any deviation from the theoretical response is a result of residual processing phenomenon and/or suboptimal processing, and a simple offsetdependent scaling function is designed to correct for these differences. This function can then be applied to seismic data over both prospective and nonprospective zones within an area where the theoretical values are appropriate and the seismic characteristics are consistent. A conservative application of the above procedure results in an AVO response over both gas sands and wet sands that is much closer to theoretically expected values. A case history from the Gulf of Mexico Flexure Trend is presented as an example to demonstrate the offset balancing technique.

scholarly journals Fault interpretation in a vertically exaggerated seismic section: evidence of conceptual model uncertainty and anchoring

2019 ◽  
Author(s):  
Juan Alcalde ◽  
Clare E. Bond ◽  
Gareth Johnson ◽  
Armelle Kloppenburg ◽  
Oriol Ferrer ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Conceptual Model ◽  
Seismic Data ◽  
Model Uncertainty ◽  
Conceptual Models ◽  
Geophysical Data ◽  
Seismic Section ◽  
Reflection Seismic ◽  
Interpretation Process ◽  
Fault Interpretation

Abstract. The use of conceptual models is essential in the interpretation of reflection seismic data. It allows interpreters to make geological sense of seismic data which carries inherent uncertainty. However, conceptual models can create powerful anchors that prevent interpreters from reassessing and adapting their interpretations as part of the interpretation process, which can subsequently lead to flawed or erroneous outcomes. It is therefore critical to understand how conceptual models are generated and applied to reduce unwanted effects in interpretation results. Here we have tested how interpretation of vertically exaggerated seismic data influenced the creation and adoption of the conceptual models of 160 participants in a paper-based interpretation experiment. Participants were asked to interpret a series of faults and a horizon, off-set by those faults, in a seismic section. The seismic section was randomly presented to the participants with different horizontal-vertical exaggeration (1 : 4 or 1 : 2). Statistical analysis of the results indicates that early anchoring to specific conceptual models had the most impact on interpretation outcome; with the degree of vertical exaggeration having a subdued influence. Three different conceptual models were adopted by participants, constrained by initial observations of the seismic data. Interpreted fault dip angles show no evidence of other constraint (e.g. from the application of accepted fault dip models). Our results provide evidence of biases in interpretation of uncertain geological and geophysical data, including the use of heuristics to form initial conceptual models and anchoring to these models, confirming the need for increased understanding and mitigation of these biases to improve interpretation outcomes.

Seismic signal recognition by unsupervised machine learning

2019 ◽  
Vol 219 (2) ◽  
pp. 1163-1180
Author(s):  
Weilin Huang
Keyword(s):  
Machine Learning ◽  
Seismic Data ◽  
Clustering Algorithm ◽  
Seismic Signal ◽  
Signal Recognition ◽  
Unsupervised Machine Learning ◽  
Reflection Seismic ◽  
Sampling Points ◽  
Data Points ◽  
Clustering Data

SUMMARY Seismic signal recognition can serve as a powerful auxiliary tool for analysing and processing ever-larger volumes of seismic data. It can facilitate many subsequent procedures such as first-break picking, statics correction, denoising, signal detection, events tracking, structural interpretation, inversion and imaging. In this study, I propose an automatic technique of seismic signal recognition taking advantage of unsupervised machine learning. In the proposed technique, seismic signal recognition is considered as a problem of clustering data points. All the seismic sampling points in time domain are clustered into two clusters, that is, signal or non-signal. The hierarchical clustering algorithm is used to group these sampling points. Four attributes, that is, two short-term-average-to-long-term-average ratios, variance and envelope are investigated in the clustering process. In addition, to quantitatively evaluate the performance of seismic signal recognition properly, I propose two new statistical indicators, namely, the rate between the total energies of original and recognized signals (RTE), and the rate between the average energies of original and recognized signals (RAE). A large number of numerical experiments show that when the signal is slightly corrupted by noise, the proposed technique performs very well, with recognizing accuracy, precision and RTE of nearly 1 (i.e. 100 per cent), recall greater than 0.8 and RAE about 1–1.3. When the signal is moderately corrupted by noise, the proposed technique can hold recognizing accuracy about 0.9, recognizing precision nearly to 1, RTE about 0.9, recall around 0.6 and RAE about 1.5. Applications of the proposed technique to real microseismic data induced from hydraulic fracturing and reflection seismic data demonstrate its feasibility and encouraging prospect.

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