Acoustic impedance estimation using a gradient-based algorithm with total variation semi-norm regularization

We present an algorithm to estimate blocky images of the subsurface acoustic impedance (AI) from seismic reflection data. We use the total variation semi-norm (TV) to regularize the inversion and promote blocky solutions which are, by virtue of the capability of TV to handle edges properly, adequate to model layered earth models with sharp contrasts. In addition, the use of the TV leads to a convex objective function that can be minimized using a gradientbased algorithm that only requires matrix-vector multiplications and no direct matrix inversion. The latter makes the algorithm numerically stable, easy to apply, and economic in terms of computational cost. Besides, given appropriate a priori information, the algorithm allows to easily incorporate into the inversion scheme the low frequency trend that is missing from the data. Numerical tests on noisy 2D synthetic and field data show that the proposed method is capable of providing consistent and blocky AI images that preserve edges and the subsurface layered structure.Facultad de Ciencias Astronómicas y Geofísica

Presentism meets black holes

Presentism is, roughly, the metaphysical doctrine that maintains that whatever exists, exists in the present. The compatibility of presentism with the theories of special and general relativity was much debated in recent years. It has been argued that at least some versions of presentism are consistent with time-orientable models of general relativity. In this paper we confront the thesis of presentism with relativistic physics, in the strong gravitational limit where black holes are formed. We conclude that the presentist position is at odds with the existence of black holes and other compact objects in the universe. A revision of the thesis is necessary, if it is intended to be consistent with the current scientific view of the universe.Facultad de Ciencias Astronómicas y Geofísica

Acoustic impedance estimation using a gradient-based algorithm with total variation semi-norm regularization

We present an algorithm to estimate blocky images of the subsurface acoustic impedance (AI) from seismic reflection data. We use the total variation semi-norm (TV) to regularize the inversion and promote blocky solutions which are, by virtue of the capability of TV to handle edges properly, adequate to model layered earth models with sharp contrasts. In addition, the use of the TV leads to a convex objective function that can be minimized using a gradientbased algorithm that only requires matrix-vector multiplications and no direct matrix inversion. The latter makes the algorithm numerically stable, easy to apply, and economic in terms of computational cost. Besides, given appropriate a priori information, the algorithm allows to easily incorporate into the inversion scheme the low frequency trend that is missing from the data. Numerical tests on noisy 2D synthetic and field data show that the proposed method is capable of providing consistent and blocky AI images that preserve edges and the subsurface layered structure.Facultad de Ciencias Astronómicas y Geofísica

Simple and fast gradient-based impedance inversion using total variation regularization

We present an algorithm to estimate blocky images of the subsurface acoustic impedance (AI) from poststack seismic data. We regularize the resulting inverse problem, which is inherently ill-posed and non-unique, by means of the total variation semi-norm (TV). This allows us promote stable and blocky solutions which are, by virtue of the capability of TV to handle edges properly, adequate to model layered earth models with sharp contrasts. The use of the TV leads to a convex objective function easily minimized using a gradient-based algorithm that requires, in contrast to other AI inversion methods based on TV regularization, simple matrix-vector multiplications and no direct matrix inversion. The latter makes the algorithm numerically stable, easy to apply, and economic in terms of computational cost. Tests on synthetic and field data show that the proposed method, contrarily to conventional l2- or l1-norm regularized solutions, is able to provide blocky AI images that preserve the subsurface layered structure with good lateral continuity from noisy observations.Facultad de Ciencias Astronómicas y Geofísica

Nuevas estrategias para la inversión sparse de datos sísmicos prestack

Uno de los objetivos centrales de la inversión de datos sísmicos prestack consiste en determinar contrastes entre las propiedades físicas de las rocas del subsuelo a partir de la información contenida en la variación en función del ángulo de incidencia de las amplitudes de las ondas sísmicas reflejadas en las interfaces geológicas. La inversión de datos sísmicos prestack es un problema mal planteado y mal condicionado, en el sentido de que pequeñas cantidades de ruido en el dato llevan a grandes inestabilidades en las soluciones estimadas. Además, debido a la naturaleza de los datos observados, que son ruidosos, incompletos y de banda limitada, coexiste el problema de la no-unicidad de las soluciones. Dichos problemas apremian la utilización de regularizaciones y restricciones con el fin de estabilizar el proceso de inversión y promover al mismo tiempo soluciones con alguna característica deseada. Las soluciones ralas, o sparse, son deseables debido a que permiten obtener reflectores bien definidos y de esa forma superar el problema de la baja resolución observada en las soluciones obtenidas por medio de métodos de inversión convencionales. En este trabajo de tesis presentamos tres nuevas estrategias basadas en la utilización de diferentes regularizaciones que estabilizan el problema de inversión y promueven soluciones sparse a partir de datos sísmicos prestack. En la primera estrategia se procede a estimar soluciones sub-óptimas del problema de inversión regularizado mediante la norma L0 por medio de la utilización del algoritmo de optimización global Very Fast Simulated Annealing (VFSA). La segunda estrategia consta de dos etapas: primero se resuelve el problema de inversión regularizado mediante la norma L1 por medio de un eficiente algoritmo de optimización conocido como Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) y luego se realiza un paso correctivo de las amplitudes estimadas utilizando mínimos cuadrados. Estas dos primeras estrategias permiten estimar con éxito soluciones sparse utilizando la aproximación de Shuey de dos términos, modelo que describe la variación con el ángulo de incidencia de los coeficientes de reflexión sísmica. La tercera estrategia utiliza como regularización la norma L1,2, permitiendo incorporar información a priori por medio de matrices de covarianza o de escala. En este caso se estiman soluciones sparse de los parámetros de la aproximación de Aki & Richards de tres términos y, si la información a priori disponible es adecuada, es posible obtener también una estimación de tipo blocky de los parámetros elásticos del subsuelo.Facultad de Ciencias Astronómicas y Geofísica

Propuesta de un sistema integrado de gestión en calidad, medio ambiente, seguridad y salud ocupacional para mejorar la rentabilidad de la empresa metalmecánica Gerdipac Industrial E.I.R.L.

El autor no autorizó la publicación de la tesis

High-resolution prestack seismic inversion using a hybrid FISTA least-squares strategy

A new inversion method to estimate high-resolution amplitude-versus-angle attributes (AVA) attributes such as intercept and gradient from prestack data is presented. The proposed technique promotes sparse-spike reflectivities that, when convolved with the source wavelet, fit the observed data. The inversion is carried out using a hybrid two-step strategy that combines fast iterative shrinkagethresholding algorithm (FISTA) and a standard least-squares (LS) inversion. FISTA, which can be viewed as an extension of the classical gradient algorithm, provides sparse solutions by minimizing the misfit between the modeled and the observed data, and the l1-norm of the solution. FISTA is used to estimate the location in time of the main reflectors. Then, LS is used to retrieve the appropriate reflectivity amplitudes that honor the data. FISTA, like other iterative solvers for l1-norm regularization, does not require matrices in explicit form, making it easy to apply, economic in computational terms, and adequate for solving large-scale problems. As a consequence, the FISTA+LS strategy represents a simple and cost-effective new procedure to solve the AVA inversion problem. Results on synthetic and field data show that the proposed hybrid method can obtain highresolution AVA attributes from noisy observations, making it an interesting alternative to conventional methods.Facultad de Ciencias Astronómicas y Geofísica

A hybrid strategy based on fast iterative shrinkage-thresholding algorithm and very fast simulated annealing: application to the prestack seismic inverse problem

With the purpose of characterizing the Earth subsurface, one of the objectives of the inversion of prestack seismic data is to determine contrasts between rock properties from the information contained in the variation of the amplitudes of the reflected compressional waves with the angle of incidence. This amplitude-versus-angle (AVA) variation can be described by various approximations to the so-called Zoeppritz equations, a set of non-linear equations that depend on the physical characteristics of the medium at each side of the interface where the compressional wave strikes. The coefficients of such approximations constitute AVA attributes that may provide important information about fluid content, a key issue for the characterization of hydrocarbon reservoirs. In this work we present a new inversion strategy to estimate efficiently and accurately high-resolution AVA attributes from prestack data. The proposed technique promotes sparse-spike reflectivities that, when convolved with the source wavelet, fit the observed data. Sparse solutions are desirable because they can be used to characterize significant and close reflectors more accurately than using conventional solutions. The inversion is carried out using a hybrid two-step strategy than combines Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) and Very Fast Simulated Annealing (VFSA). FISTA provides sparse solutions by minimizing both the misfit between the modeled and the observed data, and the l1-norm of the solution. VFSA is an stochastic computational algorithm to finding near-optimal solutions to hard optimization problems. At the first stage, FISTA sparse-solutions provide an estimate of the location in time of the main reflectors, information that is subsequently used as an initial guess for the second stage, where accurate reflectivity amplitudes are estimated by solving a more stable overdetermined inverse problem. The second stage also involves the use of VFSA for tuning the location in time of the main reflectors and the source wavelet. FISTA does not require the inversion of matrices in explicit form. At each iteration only matrix-vector multiplications are involved, making it easy to apply, economic in computational terms, and adequate for solving large-scale problems. As a result, the FISTA+VFSA strategy represents a simple and cost-effective new procedure to solve the high-resolution AVA inversion problem. Results on synthetic data show that the proposed hybrid method can obtain high-resolution AVA attributes from noisy observations, even when the number of reflectors is not known a priori and the utilized wavelet is inaccurate, making it an interesting alternative to conventional methods.Facultad de Ciencias Astronómicas y Geofísica

A hybrid strategy based on fast iterative shrinkage-thresholding algorithm and very fast simulated annealing: application to the prestack seismic inverse problem

With the purpose of characterizing the Earth subsurface, one of the objectives of the inversion of prestack seismic data is to determine contrasts between rock properties from the information contained in the variation of the amplitudes of the reflected compressional waves with the angle of incidence. This amplitude-versus-angle (AVA) variation can be described by various approximations to the so-called Zoeppritz equations, a set of non-linear equations that depend on the physical characteristics of the medium at each side of the interface where the compressional wave strikes. The coefficients of such approximations constitute AVA attributes that may provide important information about fluid content, a key issue for the characterization of hydrocarbon reservoirs. In this work we present a new inversion strategy to estimate efficiently and accurately high-resolution AVA attributes from prestack data. The proposed technique promotes sparse-spike reflectivities that, when convolved with the source wavelet, fit the observed data. Sparse solutions are desirable because they can be used to characterize significant and close reflectors more accurately than using conventional solutions. The inversion is carried out using a hybrid two-step strategy than combines Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) and Very Fast Simulated Annealing (VFSA). FISTA provides sparse solutions by minimizing both the misfit between the modeled and the observed data, and the l1-norm of the solution. VFSA is an stochastic computational algorithm to finding near-optimal solutions to hard optimization problems. At the first stage, FISTA sparse-solutions provide an estimate of the location in time of the main reflectors, information that is subsequently used as an initial guess for the second stage, where accurate reflectivity amplitudes are estimated by solving a more stable overdetermined inverse problem. The second stage also involves the use of VFSA for tuning the location in time of the main reflectors and the source wavelet. FISTA does not require the inversion of matrices in explicit form. At each iteration only matrix-vector multiplications are involved, making it easy to apply, economic in computational terms, and adequate for solving large-scale problems. As a result, the FISTA+VFSA strategy represents a simple and cost-effective new procedure to solve the high-resolution AVA inversion problem. Results on synthetic data show that the proposed hybrid method can obtain high-resolution AVA attributes from noisy observations, even when the number of reflectors is not known a priori and the utilized wavelet is inaccurate, making it an interesting alternative to conventional methods.Facultad de Ciencias Astronómicas y Geofísica

La fotografía participativa para el reforzamiento de la percepción de la realidad social y el fomento de la participación ciudadana de los estudiantes de secundaria en la Victoria

La presente propuesta académica expone una línea de investigación en base a un diseño de investigación experimental el cual se fundamenta en la metodología de la Fotografía Participativa, la cual nos ha permitido generar espacios de diálogo de estudiantes con el motivo de conocer su realidad social y fomentar propuestas de desarrollo comunitario según lo visto y dialogado. Esta investigación nace del planteamiento del problema: ¿De qué manera la Implementación de un taller de fotografía participativa influenciará en la percepción de la realidad social para fomentar la participación ciudadana de los estudiantes del cuarto año de secundaria en la Institución Educativa “Juan Pablo Vizcardo y Guzmán ZEA”?, esta pregunta es el inicio de todo lo recopilado durante el mes y medio de la realización del taller, y que ha llevado a conocer diferentes miradas de jóvenes que desde su percepción han podido capturar todo lo que los rodea a través de sus mismas fotografías. Lo relevante de esta investigación son los resultados obtenidos, siendo estos positivos tanto como para ellos como participantes y para nosotros como investigadores – facilitadores. La respuesta de cada estudiante nos ha permitido ampliar y confirmar que la fotografía participativa sí es una excelente herramienta para el cambio social, puesto que su misma veracidad y forma realista de retratar el entorno, ha permitido a los jóvenes conocer de una forma diferente lo que los rodea y de lo significante de accionar para desarrollarse como personas y sociedad