Low-frequency data analysis and expansion

2015 ◽  
Vol 12 (2) ◽  
pp. 212-220 ◽  
Author(s):  
Jun-Hua Zhang ◽  
Bin-Bin Zhang ◽  
Zai-Jin Zhang ◽  
Hong-Xian Liang ◽  
Da-Ming Ge
Keyword(s):  
Data Analysis ◽  
Low Frequency ◽  
Frequency Data

Accurate Drilling Data Interpretations Brought Significant Values to a Major Drilling Project

2021 ◽  
Author(s):  
Faisal Rashid ◽  
Hamdan Mohamed Al Saadi ◽  
Shahid Yakubbhai Duivala ◽  
Steve Butt ◽  
Sultan Al Mansoori ◽  
...  
Keyword(s):  
Data Analysis ◽  
High Frequency ◽  
Performance Enhancement ◽  
Low Frequency ◽  
High Frequency Data ◽  
Coding System ◽  
Frequency Data ◽  
Drilling Data ◽  
The Many ◽  
Drilling Project

Abstract With the launch of a mega drilling project in the Middle East, the drilling data during the execution stage was collected in two formats; Low-Frequency Data and High-Frequency Data. This paper explains the effective utilization of data in the performance enhancement scheme. The paper also demonstrates the combination of Low-frequency and High-frequency data can reveal the many secrets of the drilling operations and can open the many sides of drilling operations for improvements. Low-Frequency data was entered manually at the rig-site using an improved coding system to identify the activities start and end times. High-Frequency data was collected through real-time transmission from the different data streaming services at the rig-site. Both data forms were collected simultaneously using stringent rules and close follow-ups to make sure that data collection was free of any reporting mistakes and gaps. Later, the collected data was extracted for different types of analyses and interpretations. Low-frequency data was studied in a novel way to get the best analytical and critical outcome to make sure that the right areas for improvements were identified and actions were implemented for enhanced performance. Improved operations coding system helped the team to categorize the operations and failures in an effective way to set new standards in data analysis. More than 100 different types of analyses using the best data analysis technique, such as trailing average, normalization, trends, etc., were conducted based on the information collected during the execution phase, and many new KPIs were established with challenging milestones to be achieved in the prescribed period. High-Frequency data was split into different sets of KPIs to identify the multiple Invisible Lost Time (ILT) areas to boost the operational efficiency. Various performance enhancement schemes were developed based on High-frequency data. As a result, these schemes were proven to enhance the performance of the mega drilling project. This paper discusses the novel methods of drilling data analysis based on low and high-frequency data and shows the effectiveness of the data presented in a standardized format over a period. It deliberates how the teams were challenged to enhance the performance. Such detailed data analysis will bring valuable information for the industry to utilize the conventional database in modernized ways to get the best outcomes from the data analysis results.

Predicting risk in energy markets: Low-frequency data still matter

2021 ◽  
Vol 282 ◽  
pp. 116146
Author(s):  
Štefan Lyócsa ◽  
Neda Todorova ◽  
Tomáš Výrost
Keyword(s):  
Low Frequency ◽  
Energy Markets ◽  
Frequency Data

Denoising for full-waveform inversion with expanded prediction-error filters

Geophysics ◽  
2021 ◽  
pp. 1-54
Author(s):  
Milad Bader ◽  
Robert G. Clapp ◽  
Biondo Biondi
Keyword(s):  
High Frequency ◽  
Prediction Error ◽  
Signal To Noise Ratio ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Full Waveform Inversion ◽  
Frequency Data ◽  
Signal To Noise ◽  
Frequency Signal ◽  
Full Waveform

Low-frequency data below 5 Hz are essential to the convergence of full-waveform inversion towards a useful solution. They help build the velocity model low wavenumbers and reduce the risk of cycle-skipping. In marine environments, low-frequency data are characterized by a low signal-to-noise ratio and can lead to erroneous models when inverted, especially if the noise contains coherent components. Often field data are high-pass filtered before any processing step, sacrificing weak but essential signal for full-waveform inversion. We propose to denoise the low-frequency data using prediction-error filters that we estimate from a high-frequency component with a high signal-to-noise ratio. The constructed filter captures the multi-dimensional spectrum of the high-frequency signal. We expand the filter's axes in the time-space domain to compress its spectrum towards the low frequencies and wavenumbers. The expanded filter becomes a predictor of the target low-frequency signal, and we incorporate it in a minimization scheme to attenuate noise. To account for data non-stationarity while retaining the simplicity of stationary filters, we divide the data into non-overlapping patches and linearly interpolate stationary filters at each data sample. We apply our method to synthetic stationary and non-stationary data, and we show it improves the full-waveform inversion results initialized at 2.5 Hz using the Marmousi model. We also demonstrate that the denoising attenuates non-stationary shear energy recorded by the vertical component of ocean-bottom nodes.

scholarly journals Nonparametric estimation of scalar diffusions based on low frequency data

2004 ◽  
Vol 32 (5) ◽  
pp. 2223-2253 ◽  
Author(s):  
Markus Rei� ◽  
Marc Hoffmann ◽  
Emmanuel Gobet
Keyword(s):  
Nonparametric Estimation ◽  
Low Frequency ◽  
Frequency Data

scholarly journals Econometric Forecasting and High-Frequency Data Analysis

10.1142/6664 ◽  
2008 ◽  
Author(s):  
Roberto S Mariano ◽  
Yiu-Kuen Tse
Keyword(s):  
Data Analysis ◽  
High Frequency ◽  
High Frequency Data ◽  
Frequency Data

Low Frequency DAS Data Study with Integrated Data Analysis for Monitoring Hydraulic Fracture

2020 ◽  
Author(s):  
M. Ichikawa ◽  
M. Kato ◽  
S. Uchida ◽  
K. Tamura ◽  
A. Kato ◽  
...  
Keyword(s):  
Data Analysis ◽  
Hydraulic Fracture ◽  
Low Frequency ◽  
Integrated Data Analysis
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