Tackling an Inverse Problem from the Petroleum Industry with a Genetic Algorithm for Sampling

2004 ◽  
pp. 1299-1300 ◽  
Author(s):  
Pedro J. Ballester ◽  
Jonathan N. Carter
Keyword(s):  
Genetic Algorithm ◽  
Inverse Problem ◽  
Petroleum Industry

scholarly journals Adding Prior Information in FWI through Relative Entropy

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 599
Author(s):  
Danilo Cruz ◽  
João de Araújo ◽  
Carlos da Costa ◽  
Carlos da Silva
Keyword(s):  
Inverse Problem ◽  
Relative Entropy ◽  
Global Minimum ◽  
Prior Information ◽  
Waveform Inversion ◽  
Petroleum Industry ◽  
Synthetic Data ◽  
Full Waveform Inversion ◽  
Full Waveform

Full waveform inversion is an advantageous technique for obtaining high-resolution subsurface information. In the petroleum industry, mainly in reservoir characterisation, it is common to use information from wells as previous information to decrease the ambiguity of the obtained results. For this, we propose adding a relative entropy term to the formalism of the full waveform inversion. In this context, entropy will be just a nomenclature for regularisation and will have the role of helping the converge to the global minimum. The application of entropy in inverse problems usually involves formulating the problem, so that it is possible to use statistical concepts. To avoid this step, we propose a deterministic application to the full waveform inversion. We will discuss some aspects of relative entropy and show three different ways of using them to add prior information through entropy in the inverse problem. We use a dynamic weighting scheme to add prior information through entropy. The idea is that the prior information can help to find the path of the global minimum at the beginning of the inversion process. In all cases, the prior information can be incorporated very quickly into the full waveform inversion and lead the inversion to the desired solution. When we include the logarithmic weighting that constitutes entropy to the inverse problem, we will suppress the low-intensity ripples and sharpen the point events. Thus, the addition of entropy relative to full waveform inversion can provide a result with better resolution. In regions where salt is present in the BP 2004 model, we obtained a significant improvement by adding prior information through the relative entropy for synthetic data. We will show that the prior information added through entropy in full-waveform inversion formalism will prove to be a way to avoid local minimums.

scholarly journals Optimization of Fusion Zone Grain Size, Hardness, and Ultimate Tensile Strength of Pulsed Current Microplasma Arc Welded AISI 304L Sheets Using Genetic Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Siva Prasad Kondapalli ◽  
Srinivasa Rao Chalamalasetti ◽  
Nageswara Rao Damera
Keyword(s):  
Genetic Algorithm ◽  
Grain Size ◽  
Tensile Strength ◽  
Ultimate Tensile Strength ◽  
Process Parameters ◽  
Petroleum Industry ◽  
Design Matrix ◽  
Pulsed Current ◽  
Aisi 304L ◽  
Metal Bellows

Austenitic stainless steel sheets have gathered wide acceptance in the fabrication of components, which require high temperature resistance and corrosion resistance, such as metal bellows used in expansion joints in aircraft, aerospace, and petroleum industry. In case of single pass welding of thinner sections of this alloy, Pulsed Current Microplasma Arc Welding (PCMPAW) was found beneficial due to its advantages over the conventional continuous current process. The quality of welded joint depends on the grain size, hardness, and ultimate tensile strength, which have to be properly controlled and optimized to ensure better economy and desirable mechanical characteristics of the weld. This paper highlights the development of empirical mathematical equations using multiple regression analysis, correlating various process parameters to grain size, and ultimate tensile strength in PCMPAW of AISI 304L sheets. The experiments were conducted based on a five-factor, five-level central composite rotatable design matrix. A genetic algorithm (GA) was developed to optimize the process parameters for achieving the desired grain size, hardness, and ultimate tensile strength.

scholarly journals Improving of Data Processing Effectiveness for Pavement Structural Evaluation Using Subsurface Radar Probing

2013 ◽  
Vol 14 (2) ◽  
pp. 143-154
Author(s):  
Alexander Krainyukov ◽  
Valery Kutev
Keyword(s):  
Genetic Algorithm ◽  
Inverse Problem ◽  
Data Processing ◽  
Frequency Domain ◽  
Iterative Procedure ◽  
Search Range ◽  
Structural Evaluation ◽  
Modified Genetic Algorithm ◽  
Pavement Structure ◽  
Structure Evaluation

Problems of the data processing improving for pavement structure evaluation with help of subsurface radar probing are discussed. Iterative procedure to solve the inverse problem in frequency domain is used on the base of the genetic algorithm. For improving of data processing effectiveness it is proposed to use a modified genetic algorithm with adaptation of search range of pavement parameters. The results of reconstruction of electro-physical characteristics for model of five-layered pavement structure are presented.

Decision Choice Optimization With Genetic Algorithm in Communication Networks

2021 ◽  
pp. 328-343
Author(s):  
Driss Ait Omar ◽  
Mohamed El Amrani ◽  
Hamid Garmani ◽  
Mohamed Baslam ◽  
Mohamed Fakir
Keyword(s):  
Mathematical Modeling ◽  
Genetic Algorithm ◽  
Inverse Problem ◽  
Decision Support ◽  
Communication Networks ◽  
Service Providers ◽  
Telecommunication Networks ◽  
Essential Tool ◽  
Decision Choice

Optimization is an essential tool in the field of decision support. In this chapter, the authors study an inverse problem applied in the telecommunication networks. Indeed, in the telecommunication networks, service providers have subscription offers to customers. Since competition is strong in this sector, most of these advertising offerings, totally or partially ambiguous, are prepared to attract the attention of consumers. For this reason, customers face problems in making decisions about the choice of the operators that gives them a better report price/QoS. Mathematical modeling of this decision support problem led to the resolution of an inverse problem. More precisely, the inverse problem is to find the function of the QoS real knowing the QoS theoretical or advertising. This model will help customers who seek to know the degree of sincerity of their operators, and it is an opportunity for operators who want to maintain their resources so that they gain the trust of customers.

GENERATION OF SYMMETRICAL COLORED IMAGES VIA SOLUTION OF THE INVERSE PROBLEM OF CHEMICAL REACTIONS DISCRETE CHAOTIC DYNAMICS

2006 ◽  
Vol 16 (05) ◽  
pp. 1419-1434 ◽  
Author(s):  
V. GONTAR ◽  
O. GRECHKO
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Inverse Problem ◽  
Mathematical Models ◽  
Chemical Reactions ◽  
Chaotic Dynamics ◽  
Two Dimensional

An automatic procedure for generating colored two-dimensional symmetrical images based on the chemical reactions discrete chaotic dynamics (CRDCD) is proposed. The inverse problem of derivation of symmetrical images from CRDCD mathematical models was formulated and solved using a special type of genetic algorithm. Different symmetrical images corresponding to the solutions of a CRDCD mathematical model for which the parameters were obtained automatically by the proposed method are presented.

Improved auto-tuning niching genetic algorithm combined with grouping concept for inverse problem

2004 ◽  
Vol 19 (1-4) ◽  
pp. 561-566
Author(s):  
Jae-Kwang Kim ◽  
Sang-Yong Jung ◽  
Hyun-Kyo Jung ◽  
Song-Yop Hahn ◽  
Dong-Hyeok Cho ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Inverse Problem ◽  
Auto Tuning
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