Automated analysis of marine refraction data: A computer algorithm

Geophysics ◽  
1983 ◽  
Vol 48 (5) ◽  
pp. 582-589 ◽  
Author(s):  
C. Patrick Ervin ◽  
L. D. McGinnis ◽  
R. M. Otis ◽  
M. L. Hall

A computer algorithm is described that automates the processing of refraction data acquired by conventional, multichannel, seismic reflection profiling, beginning with the determination of the first arrival times and ending with a contoured velocity‐depth section. Traces for several closely spaced shots are first summed to suppress noise. Each stacked trace is convolved with a box operator to convert the first break to a peak that can be detected by the computer. The algorithm calculates intercept times using running averages of slopes. Depths to refractors are plotted and a velocity‐depth profile, interpolated at constant velocity intervals, is printed as a contoured cross‐section. A profile crossing Georges Bank, northwest Atlantic Ocean, is interpreted by both automatic and manual techniques for comparison.

2009 ◽  
Vol 47 (6) ◽  
Author(s):  
L. De Luca ◽  
R. De Franco ◽  
G. Biella ◽  
A. Corsi ◽  
R. Tondi

We performed an analysis of refraction data recorded in Italy since 1968 in the frame of the numerous deep seismic sounding and wide-angle reflection/refraction projects. The aims of this study are to construct a parametric database including the recording geometric information relative to each profile, the phase pickings and the results of some kinematic analyses performed on the data, and to define a reference 1D velocity model for the Italian territory from all the available refraction data. As concerns the first goal, for each seismic section we picked the P-wave first-arrival-times, evaluated the uncertainties of the arrival-times pickings and determined from each travel time-offset curve the 1D velocity model. The study was performed on 419 seismic sections. Picking was carried out manually by an algorithm which includes the computation of three picking functions and the picking- error estimation. For each of the travel time-offset curves a 1D velocity model has been calculated. Actually, the 1D velocity-depth functions were estimated in three different ways which assume: a constant velocitygradient model, a varying velocity-gradient model and a layered model. As regards the second objective of this work, a mean 1D velocity model for the Italian crust was defined and compared with those used for earthquake hypocentre locations and seismic tomographic studies by different institutions operating in the Italian area, to assess the significance of the model obtained. This model can be used in future works as input for a next joint tomographic inversion of active and passive seismic data.


2015 ◽  
Vol 18 (2) ◽  
pp. 107-113 ◽  
Author(s):  
Mustafa Senkaya ◽  
Hakan Karslı

<p class="MsoNormal" style="line-height: 200%;">The high-quality interpretation of seismic refraction data depends on the accurate and reliable identification of the first arrival times. First arrivals can be identified on a graphic or image by conventional picking, but this process depends on external factors, such as the scale and quality of the imaging data, amplitude ratio, sensitivity of the picking cursor and user experience. Under these considerations, identifying first arrivals in noisy data becomes more complex and unstable. In this study, the Cross-Correlation Technique (CCT), which is widely used in the process of analyzing reflection data, has been used to pick the first arrival times in noisy or noiseless seismic refraction data by a semi-automatic process. The CCT has reduced the dependence on user and decreased incorrect picking caused by environmental noise, displaying characteristics and scaling factors. The CCT has been tested with synthetic models with different noise contents and various field data. The Chi-square error criterion was used to assess the performance of the pickings. In addition, effects of small-time differences between the conventional picking process and the CCT have been demonstrated on a refraction tomography velocity section. Therefore, we believe that our proposed method is a useful contribution to the existing methods of first arrival picking.</p><p class="MsoNormal" style="line-height: 200%;"> </p><p class="MsoNormal" style="line-height: 200%;"><strong>Resumen</strong></p><p class="MsoNormal" style="line-height: 200%;">La buena interpretación de datos estadísticos de refracción sísmica depende de la identificación acertada y confiable de los tiempos de llegada. Los primeros tiempos de llegada se pueden identificar en un gráfico o imagen por picado convencional, pero este proceso depende de factores externos como la escala y la calidad de información de la imagen, el índice de amplitud, la sensibilidad del cursor de recolección y la experiencia del usuario. Bajo estas consideraciones, la identificación de los tiempos de llegada bajo información ruidosa se vuelve más compleja e inestable. En este estudio, la técnica de Correlación Cruzada (CCT, en inglés), que es ampliamente trabajada en el proceso de análisis de datos de reflexión, se utilizó para seleccionar los primeros tiempos de llegada en información sísmica ruidosa o no ruidosa con un proceso semiautomático. La CCT redujo la dependencia en el usuario y bajó el nivel de selección incorrecta causada por el ruido ambiental al desplegar características y factores de escala. La CCT se ha probado en modelos sintéticos con diferentes contenidos de ruidos y diversa información de campo. El error de la norma Chi-cuadrado se utilizó para evaluar el desempeño de las selecciones. En adición, los efectos de las pequeñas diferencias de tiempo entre el proceso convencional de selección y la CCT se han demostrado en una tomografía reflexiva de velocidad. Además, se estima que el método propuesto es una contribución útil a los métodos existentes de la recolección de los primeros tiempos de llegada.</p>


Geophysics ◽  
2018 ◽  
Vol 83 (6) ◽  
pp. U63-U77
Author(s):  
Bernard K. Law ◽  
Daniel Trad

An accurate near-surface velocity model is critical for weathering statics correction and initial model building for depth migration and full-waveform inversion. However, near-surface models from refraction inversion often suffer from errors in refraction data, insufficient sampling, and over-simplified assumptions used in refraction algorithms. Errors in refraction data can be caused by picking errors resulting from surface noise, attenuation, and dispersion of the first-arrival energy with offset. These errors are partially compensated later in the data flow by reflection residual statics. Therefore, surface-consistent residual statics contain information that can be used to improve the near-surface velocity model. We have developed a new dataflow to automatically include median and long-wavelength components of surface-consistent reflection residual statics. This technique can work with any model-based refraction solution, including grid-based tomography methods and layer-based methods. We modify the cost function of the refraction inversion by adding model and data weights computed from the smoothed surface-consistent residual statics. By using an iterative inversion, these weights allow us to update the near-surface velocity model and to reject first-arrival picks that do not fit the updated model. In this nonlinear optimization workflow, the refraction model is derived from maximizing the coherence of the reflection energy and minimizing the misfit between model arrival times and the recorded first-arrival times. This approach can alleviate inherent limitations in shallow refraction data by using coherent reflection data.


Sign in / Sign up

Export Citation Format

Share Document