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Convolution

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Proceedings Papers

Paper presented at the SEG/AAPG/SEPM First International Meeting for Applied Geoscience & Energy, September 26–October 1, 2021
Paper Number: SEG-2021-3583462
... Wave filed separation is a key step in vertical seismic profile (VSP) processing. Traditional methods are subject to prior assumptions and complex parameter settings, resulting in low precision and irrelevant interference information. We propose a specific convolutional neural networks (CNNs...
Proceedings Papers

Paper presented at the The 31st International Ocean and Polar Engineering Conference, June 20–25, 2021
Paper Number: ISOPE-I-21-3133
... Abstract Nowadays, the Convolution Neural Network(CNN) has been widely utilized to classify the image categories in many fields. We initially conducted some numerical trainings to figure out the applicability of machine learning in wave height prediction. A series of wave fields were produced...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3426595
... remains a challenging task. Through the application of 2(3)D spatial convolution operators, referred to as point-spread functions, efficient and flexible seismic modeling of prestack depth migrated paleokarst signatures may be obtained at a low computational cost. The present paper investigates...
Proceedings Papers

Paper presented at the The 29th International Ocean and Polar Engineering Conference, June 16–21, 2019
Paper Number: ISOPE-I-19-367
... ABSTRACT Maritime X-band radar has become a very popular tool in ocean waves remote sensing. Conventional approach is difficult to extract high-precision wave parameters. In this paper, a method for ocean wave remote sensing by using Convolution Neural Networks (CNN) is proposed. The CNN...
Proceedings Papers

Paper presented at the SPE Europec featured at 81st EAGE Conference and Exhibition, June 3–6, 2019
Paper Number: SPE-195554-MS
... Abstract Objectives/Scope Rate and pressure transient analysis is considered a routine process that has been developed and refined over many years. The underlying assumptions of linearity justify the use of superposition (in time and space), convolution and deconvolution. The reality of non...
Journal Articles
Petrophysics 59 (06): 799–810.
Paper Number: SPWLA-2018-v59n6a5
Published: 01 December 2018
... for borehole lithology interpretation as an alternative way. Convolution neural network (CNN) is a class of deep, feed-forward artificial neural networks, which has been applied to visual imagery analysis successfully. As one of the most popular and effective deep learning structures, CNN has been widely...
Proceedings Papers

Paper presented at the 2018 SEG International Exposition and Annual Meeting, October 14–19, 2018
Paper Number: SEG-2018-2995975
... , Expanded Abstracts , 1525 – 1528 , 10.1190/1.1817585 . Lecomte , I. , P. Lubrano Lavadera , C. Botter , I. Anell , S. J. Buckley , C. H. Eide , A. Grippa , V. Mascolo , and S. Kjoberg , 2016 , 2(3)-D convolution modelling of complex...
Proceedings Papers

Paper presented at the 2017 SEG International Exposition and Annual Meeting, September 24–29, 2017
Paper Number: SEG-2017-17496460
... ABSTRACT We present a new Conv-Gauss-FFT algorithm for the accurate and efficient evaluation of continuous convolutions-type integrals. Continuous convolution integrals are decomposed into a series of discrete convolutions using a hybrid Rectangle-Gaussian grid, with each discrete convolution...
Proceedings Papers

Paper presented at the 2016 SEG International Exposition and Annual Meeting, October 16–21, 2016
Paper Number: SEG-2016-13453668
... annual meeting microseismic event geophysics relation frequency convolution filter snr application noise seg seg international exposition reservoir characterization mccf correlated noise receiver correlated noise data application upstream oil & gas annual international...
Proceedings Papers

Paper presented at the 2014 SEG Annual Meeting, October 26–31, 2014
Paper Number: SEG-2014-0649
... Summary This paper proposes a new multichannel convolution model for stacked seismic data. This model supposes that the layers are horizontal and the reflection coefficients are sparse. The properties of the layer change weakly and randomly, which means that the reflection coefficients from...
Proceedings Papers

Paper presented at the 2014 SEG Annual Meeting, October 26–31, 2014
Paper Number: SEG-2014-0678
... Summary The finite-difference methods have been widely utilized in seismic wave numerical modelling, seismic imaging and inversion.we can truncate spatial convolutional counterpart of the pseudospectral methods to get finite-difference operators using truncated windows, and the properties...
Proceedings Papers

Paper presented at the 2014 SEG Annual Meeting, October 26–31, 2014
Paper Number: SEG-2014-1301
... zone, and top of reservoir. Here we formulate the ahead-of-drillbit prediction using SWD data as an inverse problem and propose a joint higher-order correlation and convolution concept for the inversion. Preliminary study using synthetic examples suggests the potential of the joint inversion approach...
Proceedings Papers

Paper presented at the 2014 SEG Annual Meeting, October 26–31, 2014
Paper Number: SEG-2014-1478
... introduce a novel method named the normalized convolution, or NC filter, which is based on a confidence estimation of the signal, to improve our signal to noise raito. The NC filter attenuates noise and enhances the continuity of seismic events. We demonstrate the effectiveness of the filter on simple...
Proceedings Papers

Paper presented at the 2014 SEG Annual Meeting, October 26–31, 2014
Paper Number: SEG-2014-0317
... allows implementation of a convolution operator that greatly decreases computational costs. calculation mgal upstream oil & gas model space modeling gravitational acceleration topography graham kent finite element gravity modeling reservoir characterization edge effect seg denver...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, September 30–October 2, 2013
Paper Number: SPE-166440-MS
... the corresponding constant flow rate response, is a commonly used pressure/flowrate cointerpretation method. However, the deconvolution process is actually a "desmoothing" process ( Horne, 2007 ), because the forward convolution equation is a smoothing function. This "desmoothing" process brings serious instability...
Proceedings Papers

Paper presented at the 2013 SEG Annual Meeting, September 22–27, 2013
Paper Number: SEG-2013-1219
... Summary Apparent attenuation resulting from interbed multiples is nicely expressed by the nonstationary convolution model proposed by Margrave (1997). Nonstationary convolution is an extension of the conventional convolutional model for nonstationary processes such as time migration, normal...
Proceedings Papers

Paper presented at the SPE Western Regional & AAPG Pacific Section Meeting 2013 Joint Technical Conference, April 19–25, 2013
Paper Number: SPE-165346-MS
... process is actually a "desmoothing" process (Horne, 2007), because the forward convolution equation is a smoothing function. This "desmoothing" process brings in serious instability issue in the mathematical solution, especially when the data are noisy. von Schroeter et al. (2004) made important...
Proceedings Papers

Paper presented at the SPE Middle East Oil and Gas Show and Conference, March 10–13, 2013
Paper Number: SPE-164307-MS
... Abstract In reality the rate of a production well is not constant and varies in time so the producing responses would be noisy. De-convolution is a method of converting a variable rate distorted pressure profile into the pressure profile for an equivalent constant rate production sequence...
Proceedings Papers

Paper presented at the 2011 SEG Annual Meeting, September 18–23, 2011
Paper Number: SEG-2011-2982
... an interpolation scheme that meets the requirements for solving ray tracing system numerically, we introduce a two-dimensional cubic convolution interpolation. It is found that the two-dimensional cubic convolution interpolation is efficient and accurate in comparison to bilinear interpolation. Also, it is found...
Proceedings Papers

Paper presented at the 2010 SEG Annual Meeting, October 17–22, 2010
Paper Number: SEG-2010-3071
... SUMMARY Due to the reduction in computational complexity, FFTs are usually performed to enable a faster convolution implementation in seismic computations. However, on current parallel computation platforms, such as multi-core processors, Graphic Processing Units (GPUs), and Field Programmable...

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