Application of very fast simulated annealing and differential evolution in the search for FO-CRS wavefield attributes

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. O81-O92
Author(s):  
German Garabito ◽  
João Carlos R. Cruz
Keyword(s):  
Global Optimization ◽  
Simulated Annealing ◽  
Differential Evolution ◽  
Seismic Data ◽  
Optimization Algorithms ◽  
Two Dimensions ◽  
Seismic Section ◽  
Data Set ◽  
Computational Costs ◽  
Very Fast Simulated Annealing

The finite-offset common-reflection-surface (FO-CRS) stack method can be used to simulate any common-offset (CO) seismic section by stacking prestack seismic data along the surfaces defined by the paraxial hyperbolic traveltime approximation. In two dimensions, the FO-CRS stacking operator depends on five kinematic wavefield attributes for every time sample of the target CO section. The main problem with this method is identifying a computationally efficient data-driven search strategy for accurately determining the best set of FO-CRS attributes that produce the optimal coherence measure of the seismic signal in the prestack data. Identifying a global optimization algorithm with the best performance is a challenge when solving this optimization problem. This is because the objective function is multimodal and involves a large volume of data, which leads to high computational costs. We introduced a comparative and competitive study through the application of two global optimization algorithms that simultaneously search the FO-CRS attributes from the prestack seismic data, very fast simulated annealing (VFSA) and the differential evolution (DE). By applying this FO-CRS stack to the Marmousi synthetic seismic data set, we have compared the performances of the two optimization algorithms with regard to their efficiency and effectiveness in estimating the five FO-CRS attributes. To analyze the robustness of the two algorithms, we apply them to real land seismic data and show their ability to find the near-optimal attributes and to improve reflection events in noisy data with a very low fold. We reveal that VFSA is efficient in reaching the optimal coherence value with the lowest computational costs, and that DE is effective and reliable in reaching the optimal coherence for determining the best five searched-for attributes. Regardless of the differences, the FO-CRS stack produces enhanced and regularized high-quality CO sections using both global optimization methods.

Improving seismic QP estimation using rock-physics constraints

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. MR187-MR198 ◽  
Author(s):  
Yi Shen ◽  
Jack Dvorkin ◽  
Yunyue Li
Keyword(s):  
Seismic Data ◽  
Closed Form Solution ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Analytical Relation ◽  
Gas Reservoir ◽  
Seismic Section ◽  
Data Set ◽  
Attenuation Model ◽  
Text Model

Our goal is to accurately estimate attenuation from seismic data using model regularization in the seismic inversion workflow. One way to achieve this goal is by finding an analytical relation linking [Formula: see text] to [Formula: see text]. We derive an approximate closed-form solution relating [Formula: see text] to [Formula: see text] using rock-physics modeling. This relation is tested on well data from a clean clastic gas reservoir, of which the [Formula: see text] values are computed from the log data. Next, we create a 2D synthetic gas-reservoir section populated with [Formula: see text] and [Formula: see text] and generate respective synthetic seismograms. Now, the goal is to invert this synthetic seismic section for [Formula: see text]. If we use standard seismic inversion based solely on seismic data, the inverted attenuation model has low resolution and incorrect positioning, and it is distorted. However, adding our relation between velocity and attenuation, we obtain an attenuation model very close to the original section. This method is tested on a 2D field seismic data set from Gulf of Mexico. The resulting [Formula: see text] model matches the geologic shape of an absorption body interpreted from the seismic section. Using this [Formula: see text] model in seismic migration, we make the seismic events below the high-absorption layer clearly visible, with improved frequency content and coherency of the events.

Processing, inversion, and interpretation of a 2D seismic data set from the North Viking Graben, North Sea

Geophysics ◽  
2003 ◽  
Vol 68 (3) ◽  
pp. 837-848 ◽  
Author(s):  
Gislain B. Madiba ◽  
George A. McMechan
Keyword(s):  
Seismic Data ◽  
Dynamic Range ◽  
Velocity Ratio ◽  
Total Porosity ◽  
Shear Velocity ◽  
Seismic Section ◽  
Data Set ◽  
Amplitude Variation With Offset ◽  
Fluid Content ◽  
The North

Simultaneous elastic impedance inversion is performed on the 2D North Viking Graben seismic data set used at the 1994 SEG workshop on amplitude variation with offset and inversion. P‐velocity (Vp), S‐velocity (Vs), density logs, and seismic data are input to the inversion. The inverted P‐impedance and S‐impedance sections are used to generate an approximate compressional‐to‐shear velocity ratio (Vp/Vs) section which, in turn, is used along with water‐filled porosity (Swv) derived from the logs from two wells, to generate fluid estimate sections. This is possible as the reservoir sands have fairly constant total porosity of approximately 28 ± 4%, so the hydrocarbon filled porosity is the total porosity minus the water‐filled porosity. To enhance the separation of lithologies and of fluid content, we map Vp/Vs into Swv using an empirical crossplot‐derived relation. This mapping expands the dynamic range of the low end of the Vp/Vs values. The different lithologies and fluids are generally well separated in the Vp/Vs–Swv domain. Potential hydrocarbon reservoirs (as calibrated by the well data) are identified throughout the seismic section and are consistent with the fluid content estimations obtained from alternative computations. The Vp/Vs–Swv plane still does not produce unique interpretation in many situations. However, the critical distinction, which is between hydrocarbon‐bearing sands and all other geologic/reservoir configurations, is defined. Swv ≤ 0.17 and Vp/Vs ≤ 1.8 are the criteria that delineate potential reservoirs in this area, with decreasing Swv indicating a higher gas/oil ratio, and decreasing Vp/Vs indicating a higher sand/shale ratio. As these criteria are locally calibrated, they appear to be valid locally; they should not be applied to other data sets, which may exhibit significantly different relationships. However, the overall procedure should be generally applicable.

Usage of Differential Evolution Algorithm in the Calibration of Parametric Rainfall-Runoff Modeling

2018 ◽  
pp. 481-499 ◽  
Author(s):  
Umut Okkan ◽  
Nuray Gedik ◽  
Halil Uysal
Keyword(s):  
Climate Change ◽  
Global Optimization ◽  
Differential Evolution ◽  
Hydrological Model ◽  
Optimization Algorithms ◽  
Differential Evolution Algorithm ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Lumped Model ◽  
Evolution Algorithm

In recent years, global optimization algorithms are used in many engineering applications. Calibration of certain parameters at conceptualization of hydrological models is one example of these. An important issue in interpreting the effects of climate change on the basin depends on selecting an appropriate hydrological model. Not only climate change impact assessment studies, but also many water resources planning studies refer to such modeling applications. In order to obtain reliable results from these hydrological models, calibration phase of the models needs to be done well. Hence, global optimization methods are utilized in the calibration process. In this chapter, the differential evolution algorithm (DEA), which has rare application in the hydrological modeling literature, was explained. As an application, the use of the DEA algorithm in the hydrological model calibration phase was mentioned. DYNWBM, a lumped model with five parameters, was selected as the hydrological model. The calibration and then validation period performances of the DEA based DYNWBM model were tested and also compared with other global optimization algorithms. According to the results derived from the study, hydrological model appropriately reflects the rainfall-runoff relation of basin for both periods.

Global optimization strategies for implementing 3D common-reflection-surface stack using the very fast simulated annealing algorithm: Application to real land data

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. V253-V261 ◽  
Author(s):  
German Garabito
Keyword(s):  
Global Optimization ◽  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Computational Cost ◽  
Velocity Model ◽  
Global Search ◽  
Optimization Strategy ◽  
Very Fast Simulated Annealing ◽  
Common Reflection Surface ◽  
Annealing Algorithm

The 3D common-reflection-surface (CRS) stack operator depends on eight kinematic wavefield attributes that must be extracted from the prestack data. These attributes are obtained by an efficient optimization strategy based on the maximization of the coherence measure of the seismic reflection events included by the CRS stacking operator. The main application of these kinematic attributes is to simulate zero-offset stacked data; however, they can also be used for regularization of the prestack data, prestack migration, and velocity model determination. The initial implementations of the 3D CRS stack used grid-search techniques to determine the attributes in several steps with the drawback that accumulated errors can deteriorate the final result. In this work, the global optimization very fast simulated annealing algorithm is used to search for the kinematic attributes by applying three optimization strategies for implementing CRS stacking: (1) simultaneous global search of five kinematic attributes of the 3D common-diffraction-surface stacking operator, (2) two-step global optimization strategy to first search for three attributes and then five attributes of the CRS stacking operator, and (3) simultaneous global search of eight kinematic attributes of the CRS operator. The proposed CRS stacking algorithms are applied to land data of the Potiguar Basin, Brazil. It is demonstrated that the one-step optimization strategy of the eight parameters produces the best results, however, with a higher computational cost.

A hybrid differential evolution and simulated annealing algorithm for global optimization

2021 ◽  
pp. 1-17
Author(s):  
Xiaobing Yu ◽  
Zhenjie Liu ◽  
XueJing Wu ◽  
Xuming Wang
Keyword(s):  
Global Optimization ◽  
Simulated Annealing ◽  
Differential Evolution ◽  
Simulated Annealing Algorithm ◽  
Optimization Problems ◽  
Local Optimum ◽  
Search Efficiency ◽  
Optimal State ◽  
Mutation Operation ◽  
Annealing Algorithm

Differential evolution (DE) is one of the most effective ways to solve global optimization problems. However, considering the traditional DE has lower search efficiency and easily traps into local optimum, a novel DE variant named hybrid DE and simulated annealing (SA) algorithm for global optimization (HDESA) is proposed in this paper. This algorithm introduces the concept of “ranking” into the mutation operation of DE and adds the idea of SA to the selection operation. The former is to improve the exploitation ability and increase the search efficiency, and the latter is to enhance the exploration ability and prevent the algorithm from trapping into the local optimal state. Therefore, a better balance can be achieved. The experimental results and analysis have shown its better or at least equivalent performance on the exploitation and exploration capability for a set of 24 benchmark functions. It is simple but efficient.

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