... geophysicist estimation interpretation reflectivity series ava misaligned gather gradient wavelet equation petroleum geology geological subdiscipline applied geoscience & energy 10 american association intercept velocity model reflector AVA attribute estimation from misaligned seismic...

... is composed of a decoder that forward models from the reflectivity series, and an encoder that inverts the convolutional operation to extract the reflectivity information. Two different autoencoder structures are demonstrated to successfully extract the true reflectivity models and capturing original source...

.... For generating ML model with high performance, the features of target seismic data must be reflected in the training data when the training dataset is numerically generated. The characteristic of reflectivity series, one of the important features of target data, was extracted from well log data in previous...

... and reflectivity series calculated from well logs show these Q estimates to be quite accurate. We apply our method to a 3D data volume acquired over the Horseshoe Atoll, TX, and find the spatially variable Q– 1 section is consistent with the lithology of the area. We believe that such Q– 1 section...

..., the error of Q model also has a negative impact on the reflectivity estimation. It can decrease the sparsity of reflectivity series in a sparse reflectivity inversion method. In this paper, we present a simultaneous inversion of Q and reflectivity using a dictionary learning method. The seismic trace...

... Presentation Time: 3:05 PM Location: Poster Station 4 Presentation Type: Poster order quadratic regularization seismic trace quadratic regularization regularization reflectivity series seg international exposition sparse-spike deconvolution seismic wavelet deconvolution reflectivity well...

... ABSTRACT We propose a new 3D structure-preserving sparse blind deconvolution in extending data bandwidth. This method iteratively estimates a source wavelet and solves reflectivity series using a sparse deconvolution constrained by 2D/3D structure preserving filter. A multidimensional Cadzow...

... at predicting rock properties from a recorded dataset (e.g., Sen 2006). This is a nonlinear inverse problem comprising (a) a forward problem which in its simplest form is the convolution between a source wavelet, which represents seismic signal sent to the subsurface, and a reflectivity series, which represents...

...: Wednesday, October 17, 2018 Start Time: 8:30:00 AM Location: 206A (Anaheim Convention Center) Presentation Type: Oral dirac basis seismic deconvolution upstream oil & gas educational setting seismic data inverse problem sacchi misfit function reflectivity series sdod outlier...

... ABSTRACT Seismic deconvolution is associated with recovering the reflectivity series from a seismic signal when the wavelet is known. In this paper, we address the problem of multichannel semiblind seismic deconvolution, where the wavelet is unknown and there is some uncertainty in the assumed...

... ABSTRACT In order to directly obtain the reflectivity series from seismic data, we develop an advanced reflectivity inversion method. The choice between and norm minimization is always difficult for the conventional reflectivity inversion methods, which also require the selection...

... constraint in frequency domain, which can wipe off the effects of wavelet and attenuation, and can help obtain high resolution reflectivity series. Synthetic example in stationary case proves that it is immune to random noise to some extent; Another synthetic example in non-stationary case demonstrates...

... towards the lower end of the spectrum. To this end, we propose to solve a TV-norm based convex optimization problem that has a global minimum and is equipped with a fast solver. The approach takes into account both the sparsity of the reflectivity series associated with a single trace, as well...

... upstream oil & gas sparsity machine learning inversion objective function reflectivity reflectivity series reservoir characterization bayesian framework wavelet castagna estimation geophysics optimization problem basis pursuit inversion Regularization Weight estimation in Basis Pursuit...

... at a limited number of layers. Using this simple observation it is possible to invert for reflectivity series and wavelets at the same time. We present results obtained on real data and compare them to traditional estimated wavelets using well-logs. artificial intelligence reflectivity series wavelet...

... processing and the other for poststack processing. The results are encouraging for further investigation. reflectivity series non-stationary signal spectrum dataset attenuation representation time-frequency spectrum continuous wavelet transform synthetic seismogram frequency noise sinha...

... the main idea as follows: at each trace, the reflectivity series obey the Cauchy distribution; across each trace, along the other space directions, the directional difference data of the reflectivity series obey the Cauchy distribution as well. With directional constraints, the multichannel inversion...

... Summary We present a new method for inversing the locations and P-impedance reflectivity series from pre-stack seismic data without NMO-correcting. Compared to the conventional pre-stack inversion, we focus on improving stability and resolution other than inversing those elastic parameters...

... crosswell seismic data inversion result realization inversion method reservoir characterization reflectivity realization bayesian inference reflectivity series reflectivity seismic data reflectivity profile artificial intelligence matching vsp seismic dataset upstream oil & gas synthetic...

... a real reflectivity series with a group of wavelets which hold different frequency bands. A first example shown in figure 1 illustrates the workflow where we apply the phase estimation on the synthetic created from the convolution of the wavelet (see figure 1a) and the real reflectivity series (see...