Interpretation advances in noisy data areas
نویسنده
چکیده
Noisy data are often resigned to the “too hard” basket, and an expectation exists that incremental improvements in processing effort and technology will slowly recover interpretation confidence over a long period of time. Fortunately, acquisition technology has improved significantly in recent years, and high-density 3D acquisition methods (multi-streamer, OBC, and land) are now able to provide an optimally sampled 3D dataset, which will facilitate a long shelf life of sophisticated processing applications. Naturally, strong challenges remain for processing success in difficult areas, but the growth of “true” 3D seismic processing algorithms (eg, pre-stack migration, SRME demultiple, and other noise attenuation tools) is a direct complement to the growth of high-density 3D acquisition methods. Overall, the applications of better acquisition and processing technology in exploration are producing larger data volumes, demanding more rigorous and sophisticated processing efforts, and requiring the input of a more diverse range of experts.
منابع مشابه
A method to solve the problem of missing data, outlier data and noisy data in order to improve the performance of human and information interaction
Abstract Purpose: Errors in data collection and failure to pay attention to data that are noisy in the collection process for any reason cause problems in data-based analysis and, as a result, wrong decision-making. Therefore, solving the problem of missing or noisy data before processing and analysis is of vital importance in analytical systems. The purpose of this paper is to provide a metho...
متن کاملمدیریت بازآموزی همتامحور پرستاران شاغل در بخشهای مراقبت ویژه
Introduction: Retraining programs for nurses are usually run as workshops and group discussions causing challenges as limitations on the number of participants, long lasting duration and high costs. Since most of these programs are taught by instructors working outside of clinical setting , it is necessary to use a method to train large groups of nurses in a short time. The purpose of t his...
متن کاملSystem Identification Based on Frequency Response Noisy Data
In this paper, a new algorithm for system identification based on frequency response is presented. In this method, given a set of magnitudes and phases of the system transfer function in a set of discrete frequencies, a system of linear equations is derived which has a unique and exact solution for the coefficients of the transfer function provided that the data is noise-free and the degrees of...
متن کاملIdentification of Cement Rotary Kiln in Noisy Condition using Takagi-Sugeno Neuro-fuzzy System
Cement rotary kiln is the main part of cement production process that have always attracted many researchers’ attention. But this complex nonlinear system has not been modeled efficiently which can make an appropriate performance specially in noisy condition. In this paper Takagi-Sugeno neuro-fuzzy system (TSNFS) is used for identification of cement rotary kiln, and gradient descent (GD) algori...
متن کاملSystem Identification Based on Frequency Response Noisy Data
In this paper, a new algorithm for system identification based on frequency response is presented. In this method, given a set of magnitudes and phases of the system transfer function in a set of discrete frequencies, a system of linear equations is derived which has a unique and exact solution for the coefficients of the transfer function provided that the data is noise-free and the degrees of...
متن کامل