Post-stack seismic data compression with multidimensional deep autoencoders

Seismic data are surveys from the Earth's subsurface with the goal of representing the geophysical characteristics from the region where they were obtained in order to be interpreted. These data can occupy hundreds of Gigabytes of storage, motivating their compression. In this work, we approach the problem of three-dimensional post-stack seismic data using models based on deep autoencoders. The deep autoencoder is a neural network that allows representing most of the information of a seismic data with a lower cost in comparison to its original representation. To the best of our knowledge, this is the rst work to deal with seismic compression using deep learning. Four compression methods for post-stack data are proposed: two based on a bi-dimensional compression, named 2D-based Seismic Data Compression(2DSC) and 2D-based Seismic Data Compression using Multi-resolution (2DSC-MR), and two based on three-dimensional compression, named 3D-based Seismic Data Compression (3DSC) and 3D-based Seismic Data Compression using Vector Quantization (3DSC-VQ). The 2DSC is our simplest method for seismic compression, in which the volume is compressed through its bi-dimensional sections. The 2DSC-MR extends the previous method by introducing the data compression in multiple resolutions. The 3DSC extends the 2DSC method by allowing the seismic data compression by using the three-dimensional volume instead of 2D slices. This method considers the similarity between sections to compress a whole volume with the cost of a single section. The 3DSC-VQ uses vector quantization aiming to extract more information from the seismic volumes in the encoding part. Our main goal is to compress the seismic data at low bit rates, attaining a high quality reconstruction. Experiments show that our methods can compress seismic data yielding PSNR values over 40 dB and bit rates below 1.0 bpv.Dados sísmicos s~ao mapeamentos da subsuperfície terrestre que têm como objetivo representar as características geofísicas da região onde eles foram obtidos de forma que possam ser interpretados. Esses dados podem ocupar centenas de Gigabytes de armazenamento, motivando sua compressão. Neste trabalho o problema de compressão de dados sísmicos tridimensionais pós-pilha é abordado usando modelos baseados em autocodificadores profundos. O autocodificador profundo é uma rede neural que permite representar a maior parte da informação contida em um dado sísmico com um custo menor que sua representação original. De acordo com nosso conhecimento, este é o primeiro trabalho a lidar com compressão de dados sísmicos utilizando aprendizado profundo. Dessa forma, através de aproximações sucessivas, são propostos quatro métodos de compressão de dados tridimensionais pós-pilha: dois baseados em compressão bidimensional, chamados Método de Compressão 2D de Dado Sísmico (2DSC) e Método de Compressão 2D de Dado Sísmico usando Multi-resolução (2DSC-MR), e dois baseados em compressão tridimensional, chamados Método de Compressão 3D de Dado Sísmico (3DSC) e Método de Compressão 3D de Dado Sísmico usando Quantização Vetorial (3DSC-VQ). O método 2DSC é o nosso método de compressão do dado sísmico mais simples, onde o volume é comprimido a partir de suas seções bidimensionais. O método 2DSC-MR estende o método anterior introduzindo a compressão do dado em múltiplas resoluções. O método 3DSC estende o método 2DSC permitindo a compressão do dado sísmico em sua forma volumétrica, considerando a similaridade entre seções para representar um volume inteiro com o custo de apenas uma seção. O método 3DSC-VQ utiliza quantização vetorial para relaxar a etapa de codificação do método anterior, dando maior liberdade à rede para extrair informação dos volumes sísmicos. O objetivo deste trabalho é comprimir o dado sísmico a baixas taxas de bits e com alta qualidade de reconstrução em termos de PSNR e bits-por-voxel (bpv). Experimentos mostram que os quatro métodos podem comprimir o dado sísmico fornecendo valores de PSNR acima de 40 dB a taxas de bits abaixo de 1.0 bpv.CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superio

Seismic Image Analysis Using Local Spectra

This report considers a problem in seismic imaging, as presented by researchers from Calgary Scientific Inc. The essence of the problem was to understand how the S-transform could be used to create better seismic images, that would be useful in identifying possible hydrocarbon reservoirs in the earth. The important first step was to understand what aspect of the imaging problem we were being asked to study. However, since we would not be working directly with raw seismic data, traditional seismic techniques would not be required. Rather, we would be working with a two dimensional image, either a migrated image, a common mid-point (CMP) stack, or a common depth point (CDP) stack. In all cases, the images display the subsurface of the earth with geological structures evident in various layers. For a given image the local spectrum is computed at each point. The various peaks in the spectrum are used to classify each pixel in the original seismic image resulting in an enhanced and hopefully more useful seismic pseudosection. Thus, the objective of this project was to improve the identification of layers and other geological structures apparent in the two dimensional image (a seismic section, or CDP gather) by classifying and coloring image pixels into groups based on their local spectral attributes

Applications of aerospace technology to petroleum extraction and reservoir engineering

Through contacts with the petroleum industry, the petroleum service industry, universities and government agencies, important petroleum extraction problems were identified. For each problem, areas of aerospace technology that might aid in its solution were also identified, where possible. Some of the problems were selected for further consideration. Work on these problems led to the formulation of specific concepts as candidate for development. Each concept is addressed to the solution of specific extraction problems and makes use of specific areas of aerospace technology

Chapitre 2 • Well seismic surveying

Approaches that are typically applied in deep exploration geophysics, combining different seismic and logging methods, can be technically adapted for certain geotechnical or hydrogeological surveys or some site characterizations in the framework of seismic hazard studies. Currently it is entirely feasible to implement this type of geophysical surveying if the situation requires. After reviewing the current state of knowledge regarding borehole measurements of subsurface shear velocities applied to the geotechnical field, this book illustrates the feasibility of carrying out vertical seismic profiles (VSPs) and logs in this field. This approach also illustrates the value of combining velocity measurements of formations provided by borehole seismic tools (VSP) and acoustic (sonic) tools. An innovative example of the application of borehole seismic and logging methods is then presented in the case study of a relatively near-surface (from 20 to 130 m) karst carbonate aquifer. It shows how a multi-scale description of the reservoir can be carried out by integrating the information provided by different 3D-THR surface seismic methods, full waveform acoustic logging, VSP with hydrophones, borehole optical televiewer and flow measurements. In this book the authors provide readers with guidelines to carry out these operations, in terms of acquisitions as well as processing and interpretation. Thus, users will be able to draw inspiration to continue transferring petroleum techniques and other innovative methods for use in near-surface studies