Os resultados, usando um método de sensoriamento inspirado na linha lateral dos peixes, mostram que se pode reconstruir satisfatoriamente uma imagem sísmica com metade dos dados convencionais de aquisição que usa todos os sensores iguais idênticos.
Inspirado na bioengenharia, da linha lateral dos peixes, foi desenvolvido uma nova metodologia dos dados de uma aquisição convencional que usa ao imageamento sísmico em frequência: a técnica AFA (aquisição de frequência alternada). O novo método é adequadamente comparado com uma inversão FWI convencional. A principal vantagem da técnica AFA é uma redução significativa na aquisição de dados, em vez de usar um conjunto de n sensores idênticos, empregou-se os sensores com 𝑛
2 passa-alta e 𝑛
2 passa-baixa.
Utilizando o modelo de velocidade Marmousi foi testada a inversão sísmica para vários arranjos de sensores alternados com passa-alta e passa-baixa e os resultados são bastante promissores, a imagem reconstruída é tão boa ou mesmo melhor do que a aquisição convencional. A superioridade da técnica AFA é observada na inspeção visual da imagem sísmica, especialmente no imageamento de litofácies profundas. Além disso, a função objetivo correspondente à técnica AFA mostra uma convergência melhor quando comparada com o método convencional. Finalmente, as estatísticas testadas: média, desvio padrão, erro relativo, e a semelhança estrutural são superiores para a técnica AFA.
A filtragem e o processamento de uma enorme quantidade de informação de uma forma eficiente e econômica é uma tarefa essencial do sistema nervoso. A tecnologia de geofísica de exploração pode usar essa experiência fruto da evolução biológica para otimizar a aquisição sem perder informações relevantes da subsuperfície. A estratégia apresentada neste trabalho abre uma nova perspectiva no processamento de imagem sísmica usando diferentes geometrias de sensores de passa-banda para reduzir a aquisição de dados e melhorar a resolução de imagem sísmica na geofísica.
79
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ARTIGO PUBLICADO NA REVISTA PLOS ONE
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0213847
Using fish lateral line sensing to
improve seismic acquisition and
processing
Francisco Wilton de Freitas Silva , Sérgio Luiz Eduardo Ferreira da Silva , Marcos Vinícius Cândido Henriques , Gilberto Corso
Published: April 16, 2019
89 Abstract
Bioengineering, which studies the principles and design of biological systems, is a field that has inspired the development of several technologies that are currently in use. In this work, we use concepts from the fish lateral line sensing mechanism and apply them to seismic imaging processing. The lateral line is a sensory system composed of an integrated array of mechanical sensors spanning along the fish body. We compare the array of sensors along body fish with the seismic acquisition, which employs an array of equally spaced identical mechanical sensors to image the Earth’s subsurface. In both situations, the mechanical sensors capture and process mechanical vibrations from the environment to produce useful information. We explore the strategy of using the low-pass and high-pass sensors schema of fish lateral line to improve the seismic technique. We use the full-wave inversion method to compare the conventional acquisition procedure of identical sensors with alternative sets of different sensors, which mimics the fish lateral line. Our results show that the alternate sensors arrangement surpasses the performance of the conventional acquisition method, using just half of the input information. The results point at an image processing technique that is computationally more efficient and economical than the usual seismic processing method.
90
Citation: Freitas Silva FWd, da Silva SLEF, Henriques MVC, Corso G (2019) Using fish
lateral line sensing to improve seismic acquisition and processing. PLoS ONE 14(4): e0213847. https://doi.org/10.1371/journal.pone.0213847
Editor: Haroldo V. Ribeiro, Universidade Estadual de Maringa, BRAZIL
Received: October 17, 2018; Accepted: March 2, 2019; Published: April 16, 2019
Copyright: © 2019 Freitas Silva et al. This is an open access article distributed under the
terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: Data available on line. (http://www.agl.uh.edu/downloads/marmousi2/marmousi2.html) See also the reference: @article{marmousi, title={Marmousi2: An elastic upgrade for Marmousi}, author={Gary S. Martin and Robert Wiley and Kurt J. Marfurt}, journal={The Leading Edge}, volume={25}, number={2}, pages={156-166}, year={2006}, publisher={SEG}}.
Funding: Gilberto Corso have received funding from the CNPq (Conselho Nacional de
Pesquisa), Brazil (Grant Gilberto Corso: 309246/2016-4, Sponsor agency: CNPq, Conselho Nacional de Pesquisa Científica, https://www.cnpq.br/, Title project: Técnica de Imageamento Sísmico inspirado na Bioengenharia da linha lateral dos peixes, Seismic imaging inspired in the Bioengeneering of fish lateral line). Gilberto Corso, Sérgio L. E. F. da Silva, and Marcos V. C. Henriques have received fellowship and support given by ANP through the R&D levy regulation. ANP is the Brazilian Agency of Petroleum. The Shell Company has participated with the ANP in the funding (Code number: 412017, Project Title: Novos Métodos de exploração sísmica por inversão completa das formas de onda, New methods of seismic explorations using complete waveforms inversion. The sponsor is 08.469.280/0001-93—
FUNDACAO NORTE RIOGRANDENSE DE PESQUISA E CULTURA*-
FUNPEC, https://sigfundacao.funpec.br. The sponsor is 02.681.185/0001-72—BG E&P BRASIL LTDA, https://www.shell.com.br/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
In general, seismic exploration techniques rely on the collection of massive volumes of data, which requires significant computing power [1]. Recently, a study was conducted on reducing seismic acquisition without losing information by using compressive sensing methods [2]. In this work, we explore ways to reduce data acquisition using fish lateral sensing inspired
91
methods. In fact, the observation and study of animal sensing have inspired scientists and engineers to develop innovative imaging equipment. The most well-known achievements of bioengineering in terms of sensing are the radar and sonar, which were inspired from bats and dolphins sensors [3]. In this paper, we study an animal sensing strategy that improves the imaging methods used in seismology and exploration geophysics.
The imaging of the subsurface is a topic of great scientific and economical interest [4, 5]. The most important imaging method involves capturing the reflection and refraction of seismic waves artificially produced on the surface. The usual schema consists of an explosive source and several geophones (in aquatic environment, hydrophones are used) that receive the waves reflected from the layers of the Earth’s subsurface. Fig 1(a) illustrates the main design of the seismic exploration methodology showing the wave propagating in the subsurface and being recorded by several hydrophones. In this figure, we depict a set of equally spaced identical sensors, corresponding to the basic acquisition schema in seismic exploration. The use of equally spaced identical sensors is the general schema in geophysics; however, in this work, we question the paradigm of the array of identical sensors.
Fig 1. Sketch of a typical seismic exploration showing a source and an array of hydrophones.
The propagated waves reflected in the geologic layers are indicated by rays that are reflected at the interface between different media. In (a), we present a conventional schema with identical sensors, while in (b), we show our acquisition design consisting of alternate sets of low-pass and high-pass sensors (represented by triangles of different colors).
https://doi.org/10.1371/journal.pone.0213847.g001
Full-waveform inversion (FWI) is a seismic imaging methodology that reconstructs the subsurface using the information of the propagated mechanical wave reflected by the geologic layers [6]. The FWI strategy is to solve the wave equation itself and match the result of the computed wave with the observed data from the geophones [5]. The main challenge of FWI is that it is an ill-posed inverse problem. Using the language of inversion problems, many models fit the observed data and we have to choose the best one. Besides, the huge amount of data produced in the geophones and the numerical difficulties of treating large matrices make the FWI a challenging problem.
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To tackle the sensor acquisition and FWI problem, we search for inspiration in biology, and study the lateral line, an animal organ sense. This sensing system, which is mostly present in fish but is also found in mollusks and amphibians, is composed of an array of integrated mechanical sensors [7, 8]. The fish lateral line is basically formed of arrays of pressure gradient sensors along the fish body, interconnected by nervous fibers. The fish lateral line has numerous behavioral uses: fish schooling [9], catching preys [10], fish communication [11], orientation to water flows [12], we also call attention to the lateral line imaging or hydrodynamic imaging by the lateral line [13–15]. Moreover, physiological studies show that the mechanical sensors along the lateral line may respond to different frequencies. This fact is rather surprising from a genetic perspective, since it will be cheaper for the organism to design a unique frequency response sensor type; however, actual organisms produce different kinds of pass-band sensors that respond better around 10Hz, 40Hz, or 100Hz [16]. In this manuscript, we explore an array of sensors with distinct frequency response for seismic image processing.
In this work, we develop an innovative method of seismic imaging bio-inspired in the fish lateral line, instead of the trivial all equal sensor line used in exploratory geophysics, we develop an Alternative Frequency Acquisition (AFA) array that responds to different frequency bands. The animal sensing strategy of using regions of low/high frequency band frequency sensors is a consequence of hundreds of millions of years of evolution of animal life. We remark that fishes are among the oldest vertebrate animal taxon, and dates back to 450 million years ago [17]. For the sake of comparison, the early cetacea evolved from terrestrial mammals 50 million years ago, and the dolphins, much later [18]. In this way, the dolphin sonar has a shorter time history than the evolutionary period of the fish lateral line. For this reason, we can hypothesize that nature had plenty of time to adapt an optimal acquisition mechanism for the fish lateral line. Moreover, we understand the sensing acquisition mechanism from a neuroscience perspective, as a mechanism with the ability to acquire, compute, and process information. The animal nervous system has evolved to work as a complex system that has to sense the environment, process the information, and respond