Multiple eliminations (de-multiple) are one of seismic processing steps to remove their effects and delineate the correct primary refractors. Using normal move out to flatten primaries is the way to eliminate multiples through transforming these data to frequency-wavenumber domain. The flatten primaries are aligned with zero axis of the frequency-wavenumber domain and any other reflection types (multiples and random noise) are distributed elsewhere. Dip-filter is applied to pass the aligned data and reject others will separate primaries from multiple after transforming the data back from frequency-wavenumber domain to time-distance domain. For that, a suggested name for this technique as normal move out- frequency-wavenumber domain method for multiple eliminations. The method is tested on a fake reflection event to authorize their validity, and applied to a real field X-profile 2D seismic data from southern Iraq. The results ensure the possibility of internal multiple types existing in the deep reflection data in Iraq and have to remove. So that the interpretation for the true reflectors be valid. The final processed stacked seismic data using normal move out- frequency-wavenumber domain technique shows good, clear, and sharp reflectors in comparison with the conventional normal move out stack data. Open-source Madagascar reproducible package is used for processing all steps of this study and the package is very efficient, accurate, and easy to implement normal move out, frequency-wavenumber domain, Dip-filter programs. The aim of the current study is to separate internal multiples and noise from the real 2D seismic data.
The present study was conducted with a view to determine whether focal laser therapy result in visual recovery and regression of macular edema in patients with non proliferative diabetic retinopathy and maculopathy ,and whether combined focal and scatter laser therapy in patients with proliferative diabetic retinopathy and maculopathy results in visual recovery ,regression of macular edema and regression of the risk factors. In the present work, a frequency doubled Nd: YAG laser was used for the treatment of diabetic retinopathy. The study evaluates 41 eyes of 33 diabetic patients both with Insulin Dependent Diabetes Mellitus IDDM, (n=16) and Non Insulin Dependent Diabetes Mellitus NIDDM, (n=17) with diabetic retinopathy divided into two
... Show MoreArtificial Neural Network (ANN) model's application is widely increased for wastewater treatment plant (WWTP) variables prediction and forecasting which can enable the operators to take appropriate action and maintaining the norms. It is much easier modeling tool for dealing with complex nature WWTP modeling comparing with other traditional mathematical models. ANN technique significance has been considered at present study for the prediction of sequencing batch reactor (SBR) performance based on effluent's (BOD5/COD) ratio after collecting the required historical daily SBR data for two years operation (2015-2016) from Baghdad Mayoralty and Al-Rustamiya WWTP office, Iraq. The prediction was gotten by the application of a feed-forwa
... Show MoreThis paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.
These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that. The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce
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