Tomographic reconstruction of near‐borehole slowness using refracted borehole sonic arrivals

Geophysics ◽  
1993 ◽  
Vol 58 (12) ◽  
pp. 1726-1738 ◽  
Author(s):  
Brian E. Hornby

Two‐dimensional (2-D) reconstructions of the near‐borehole slowness field are computed using arrival times of refracted borehole sonic arrivals. First‐arrival traveltimes, derived from both computer simulations and field data from full‐waveform sonic tools, were inverted for the near‐borehole formation slowness both axially along the borehole and radially away from the borehole. The inversion is nonlinear; the solution is obtained by means of a series of linear inversions followed by provisional ray tracings. Each iteration involves the application of a tomographic reconstruction algorithm similar to those used in seismic crosswell tomography or medical imaging applications. The technique was demonstrated using ray‐theoretic examples to simulate radial variations in slowness. In addition, full‐waveforms were generated using two‐and‐a‐half‐dimensional (2.5-D) FDM computer models. The finite‐difference method (FDM) computer models were used to test the validity of the ray‐theoretic approximation used in the inversion scheme and to simulate the full‐waveform sonic tool response for both radial and axial changes in formation properties. Field data examples highlighted radial changes in formation slowness caused by two separate mechanisms: water take up by swelling shales and the mechanical breakdown of the near‐borehole rock resulting from stress relief caused by the drilling process. Finally, refracted sonic arrivals from near‐borehole bed boundaries were identified in a horizontal well setting. Using refractions arriving beyond the headwave, a 2-D map of formation slowness was computed in the reservoir away from the borehole. Interpretation of the slowness map resulted in an estimation of the stand‐off of the horizontal borehole from the reservoir boundary.

Geophysics ◽  
2007 ◽  
Vol 72 (5) ◽  
pp. J53-J64 ◽  
Author(s):  
Jacques R. Ernst ◽  
Alan G. Green ◽  
Hansruedi Maurer ◽  
Klaus Holliger

Crosshole radar tomography is a useful tool in diverse investigations in geology, hydrogeology, and engineering. Conventional tomograms provided by standard ray-based techniques have limited resolution, primarily because only a fraction of the information contained in the radar data (i.e., the first-arrival times and maximum first-cycle amplitudes) is included in the inversion. To increase the resolution of radar tomograms, we have developed a versatile full-waveform inversion scheme that is based on a finite-difference time-domain solution of Maxwell’s equations. This scheme largely accounts for the 3D nature of radar-wave propagation and includes an efficient method for extracting the source wavelet from the radar data. After demonstrating the potential of the new scheme on two realistic synthetic data sets, we apply it to two crosshole field data sets acquired in very different geologic/hydrogeologic environments. These are the first applications of full-waveform tomography to observed crosshole radar data. The resolution of all full-waveform tomograms is shown to be markedly superior to that of the associated ray tomograms. Small subsurface features a fraction of the dominant radar wavelength and boundaries between distinct geological/hydrological units are sharply imaged in the full-waveform tomograms.


Geophysics ◽  
2008 ◽  
Vol 73 (5) ◽  
pp. VE93-VE100 ◽  
Author(s):  
James L. Simmons

A linear least-squares inversion is applied to the turning-ray first-arrival times of a shallow-marine seismic reflection data set to estimate the slowly varying (laterally and vertically) components of the near-surface velocity field. The velocity model is represented with a low-spatial-frequency parameterization (2D cubic B-splines) designed specifically for the predicted components of the data. This model parameterization effectively decouples the slowly varying background from the higher spatial-frequency component of the velocity field produced by shallow, low-velocity, gas-charged sands and allows the solution to be obtained in a single iteration. The observed first-arrival times (background and shallow anomaly-induced perturbations) and the slowly varying first-arrival times related to the background velocity are inverted separately. Similar velocity-model estimates result, demonstrating the decoupling imposed by the B-spline model parameterization. The background velocity and the low-velocity anomalies are best treated as separate inverse problems using very different model parameterizations. Ray tracing a synthetic model containing local low-velocity anomalies embedded in a smooth background does not accurately predict the anomaly-induced first-arrival time perturbations seen in the field data. Acoustic finite-difference waveform modeling shows that reflections and diffractions from the anomalies interfere with the diving-wave first arrivals. First-arrival times picked from the full-waveform synthetics more accurately predict the field data first-arrival times.


Geophysics ◽  
1992 ◽  
Vol 57 (2) ◽  
pp. 353-362 ◽  
Author(s):  
Livia J. Squires ◽  
Samuel N. Blakeslee ◽  
Paul L. Stoffa

Seismic first arrival times from crosshole, VSP, and reversed VSP (RVSP) experiments are collectively inverted by least‐squares for the velocity distribution between two boreholes. The tomographic reconstruction exhibits a large lateral velocity contrast that is not supported by the surface reflection data from the same location. After examining the traveltime residuals from the three tomographic datasets separately, we conclude that the velocity contrast is due primarily to static delays in the RVSP first arrival times. When a first‐order correction is made for the statics, tomographic inversion results in a velocity reconstruction that is more consistent with the surface reflection data. To isolate the velocity errors produced by the RVSP statics, we compute a residual tomogram by subtracting the statics adjusted tomogram from the original. The residual tomogram shows that the statics introduce errors not only in the region sampled by the RVSP rays, but they indirectly contaminate other regions of the tomogram as well. We reproduce this velocity error distribution as part of a model study designed to simulate the effects of statics on tomographic velocity reconstructions. Results indicate that traveltime errors on the order of 2 percent can result in tomographic velocity errors of up to 7 percent.


2021 ◽  
Vol 11 (14) ◽  
pp. 6460
Author(s):  
Fabio Di Martino ◽  
Patrizio Barca ◽  
Eleonora Bortoli ◽  
Alessia Giuliano ◽  
Duccio Volterrani

Quantitative analyses in nuclear medicine are increasingly used, both for diagnostic and therapeutic purposes. The Partial Volume Effect (PVE) is the most important factor of loss of quantification in Nuclear Medicine, especially for evaluation in Region of Interest (ROI) smaller than the Full Width at Half Maximum (FWHM) of the PSF. The aim of this work is to present a new approach for the correction of PVE, using a post-reconstruction process starting from a mathematical expression, which only requires the knowledge of the FWHM of the final PSF of the imaging system used. After the presentation of the theoretical derivation, the experimental evaluation of this method is performed using a PET/CT hybrid system and acquiring the IEC NEMA phantom with six spherical “hot” ROIs (with diameters of 10, 13, 17, 22, 28, and 37 mm) and a homogeneous “colder” background. In order to evaluate the recovery of quantitative data, the effect of statistical noise (different acquisition times), tomographic reconstruction algorithm with and without time-of-flight (TOF) and different signal-to-background activity concentration ratio (3:1 and 10:1) was studied. The application of the corrective method allows recovering the loss of quantification due to PVE for all sizes of spheres acquired, with a final accuracy less than 17%, for lesion dimensions larger than two FWHM and for acquisition times equal to or greater than two minutes.


Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. R1-R10 ◽  
Author(s):  
Zhendong Zhang ◽  
Tariq Alkhalifah ◽  
Zedong Wu ◽  
Yike Liu ◽  
Bin He ◽  
...  

Full-waveform inversion (FWI) is an attractive technique due to its ability to build high-resolution velocity models. Conventional amplitude-matching FWI approaches remain challenging because the simplified computational physics used does not fully represent all wave phenomena in the earth. Because the earth is attenuating, a sample-by-sample fitting of the amplitude may not be feasible in practice. We have developed a normalized nonzero-lag crosscorrelataion-based elastic FWI algorithm to maximize the similarity of the calculated and observed data. We use the first-order elastic-wave equation to simulate the propagation of seismic waves in the earth. Our proposed objective function emphasizes the matching of the phases of the events in the calculated and observed data, and thus, it is more immune to inaccuracies in the initial model and the difference between the true and modeled physics. The normalization term can compensate the energy loss in the far offsets because of geometric spreading and avoid a bias in estimation toward extreme values in the observed data. We develop a polynomial-type weighting function and evaluate an approach to determine the optimal time lag. We use a synthetic elastic Marmousi model and the BigSky field data set to verify the effectiveness of the proposed method. To suppress the short-wavelength artifacts in the estimated S-wave velocity and noise in the field data, we apply a Laplacian regularization and a total variation constraint on the synthetic and field data examples, respectively.


2021 ◽  
Vol 17 (1) ◽  
pp. e1008545
Author(s):  
Jun Li ◽  
Juliane Manitz ◽  
Enrico Bertuzzo ◽  
Eric D. Kolaczyk

We investigate the source detection problem in epidemiology, which is one of the most important issues for control of epidemics. Mathematically, we reformulate the problem as one of identifying the relevant component in a multivariate Gaussian mixture model. Focusing on the study of cholera and diseases with similar modes of transmission, we calibrate the parameters of our mixture model using human mobility networks within a stochastic, spatially explicit epidemiological model for waterborne disease. Furthermore, we adopt a Bayesian perspective, so that prior information on source location can be incorporated (e.g., reflecting the impact of local conditions). Posterior-based inference is performed, which permits estimates in the form of either individual locations or regions. Importantly, our estimator only requires first-arrival times of the epidemic by putative observers, typically located only at a small proportion of nodes. The proposed method is demonstrated within the context of the 2000-2002 cholera outbreak in the KwaZulu-Natal province of South Africa.


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