The role of geosteering in developing the Pyrenees Field

2014 ◽  
Vol 54 (2) ◽  
pp. 494
Author(s):  
Mark Woodall ◽  
Grant Skinner ◽  
Mauro Viandante ◽  
Laura Pontarelli ◽  
Konstantinos Kostas ◽  
...  
Keyword(s):  
Path Planning ◽  
Real Time ◽  
3D Seismic ◽  
Time Data ◽  
Associated Gas ◽  
Excellent Quality ◽  
Viscous Oil ◽  
Gas Bearing ◽  
3D Seismic Data

The Pyrenees Field comprises a series of biodegraded 19° API oil accumulations reservoired in Early Cretaceous sandstones of the Pyrenees Member in the Exmouth Sub-Basin, offshore WA The reservoir comprises excellent quality, poorly consolidated shallow marine to deltaic sands. Variable thickness oil columns (some with associated gas caps), strong bottom water drive, and relatively viscous oil has necessitated the drilling of long (up to 2,000 m) horizontal wells to maximise reservoir exposure while geosteering well to within a few meters of the roof of the reservoir to maximise standoff from the OWCs. The field is covered by excellent quality 3D seismic data; however, pre-drill mapping for well path planning is complicated by the unconformable nature of the top reservoir boundary formed by the sub-cropping Pyrenees Member. Faulting within and localised velocity variations above the reservoir are also a challenge to pre-drill well planning. Cutting-edge geosteering tools have been used to achieve the desired well paths. The tools use azimuthal deep induction resistivity measurements to model and predict reservoir and fluid boundaries, taking advantage of the large resistivity contrasts between the overlying sealing mudstones of the Muderong Formation and the oil (and occasionally gas) bearing Pyrenees reservoir sands. This extended abstract discusses the application of the tools both in pre-drill well path planning and the real-time geosteering operation. Operations are managed between the rig and a sub-surface team located in a dedicated geosteering room onshore. Here real-time data is compared with planned well paths in 3D seismic and geocellular reservoir models and well path adjustments made to optimise final well placement.

Application of 3D seismic attributes to optimize the placement of horizontal wells within a tight gas sand reservoir, Ordos Basin, China

Geophysics ◽  
2016 ◽  
Vol 81 (3) ◽  
pp. B77-B86 ◽  
Author(s):  
Zhiguo Wang ◽  
Jinghuai Gao ◽  
Xiaolan Lei ◽  
Xiaojie Cui ◽  
Daxing Wang
Keyword(s):  
Seismic Data ◽  
Ordos Basin ◽  
Horizontal Wells ◽  
Tight Gas ◽  
3D Seismic ◽  
Seismic Attribute ◽  
Horizontal Drilling ◽  
The Ordos Basin ◽  
Gas Bearing ◽  
3D Seismic Data

The Lower Permian Xiashihezi Formation in the Ordos Basin, China, is a quartz-sandstone reservoir with low porosity and low permeability. We have acquired 3D seismic data and well data from 18 vertical and four horizontal wells to indicate the potential of seismic attribute analyses in locating seismic sweet spots for lateral placement of horizontal wells. Using the analytic wavelet transform with a Morse wavelet, the integration of high tuning spectral components, high sweetness and high spectral attenuation helped us to estimate the distribution of gas-bearing tight sands in the Xiashihezi Formation. Our results revealed that the principal target of horizontal drilling and production was gas-bearing massive point bars in the braided river delta setting of the Ordos Basin. The integrated workflow of the seismic attribute analysis contributes to the optimal horizontal well planning by mining and exposing critical geological information of a tight gas sand reservoir from within 3D seismic data.

scholarly journals Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence

2019 ◽  
Vol 20 (4) ◽  
pp. e170-e200 ◽  
Author(s):  
Katja Heinisch ◽  
Rolf Scheufele
Keyword(s):  
Real Time ◽  
Optimal Combination ◽  
Financial Data ◽  
Time Data ◽  
Hard Data ◽  
Forecasting Performance ◽  
Real Time Data ◽  
Final Data ◽  
Release Data

Abstract In this paper, we investigate whether differences exist among forecasts using real-time or latest-available data to predict gross domestic product (GDP). We employ mixed-frequency models and real-time data to reassess the role of surveys and financial data relative to industrial production and orders in Germany. Although we find evidence that forecast characteristics based on real-time and final data releases differ, we also observe minimal impacts on the relative forecasting performance of indicator models. However, when obtaining the optimal combination of soft and hard data, the use of final release data may understate the role of survey information.

scholarly journals Sensors and tribological systems: applications for industry 4.0

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saquib Rouf ◽  
Ankush Raina ◽  
Mir Irfan Ul Haq ◽  
Nida Naveed
Keyword(s):  
Real Time ◽  
Industry 4.0 ◽  
Developing Economies ◽  
Industrial Applications ◽  
Vital Role ◽  
Critical Parameters ◽  
Time Data ◽  
Content Type ◽  
Real Time Data

Purpose The involvement of wear, friction and lubrication in engineering systems and industrial applications makes it imperative to study the various aspects of tribology in relation with advanced technologies and concepts. The concept of Industry 4.0 and its implementation further faces a lot of barriers, particularly in developing economies. Real-time and reliable data is an important enabler for the implementation of the concept of Industry 4.0. For availability of reliable and real-time data about various tribological systems is crucial in applying the various concepts of Industry 4.0. This paper aims to attempt to highlight the role of sensors related to friction, wear and lubrication in implementing Industry 4.0 in various tribology-related industries and equipment. Design/methodology/approach A through literature review has been done to study the interrelationships between the availability of tribology-related data and implementation of Industry 4.0 are also discussed. Relevant and recent research papers from prominent databases have been included. A detailed overview about the various types of sensors used in generating tribological data is also presented. Some studies related to the application of machine learning and artificial intelligence (AI) are also included in the paper. A discussion on fault diagnosis and cyber physical systems in connection with tribology has also been included. Findings Industry 4.0 and tribology are interconnected through various means and the various pillars of Industry 4.0 such as big data, AI can effectively be implemented in various tribological systems. Data is an important parameter in the effective application of concepts of Industry 4.0 in the tribological environment. Sensors have a vital role to play in the implementation of Industry 4.0 in tribological systems. Determining the machine health, carrying out maintenance in off-shore and remote mechanical systems is possible by applying online-real-time data acquisition. Originality/value The paper tries to relate the pillars of Industry 4.0 with various aspects of tribology. The paper is a first of its kind wherein the interdisciplinary field of tribology has been linked with Industry 4.0. The paper also highlights the role of sensors in generating tribological data related to the critical parameters, such as wear rate, coefficient of friction, surface roughness which is critical in implementing the various pillars of Industry 4.0.

scholarly journals Real-time detection of neural oscillation bursts allows behaviourally relevant neurofeedback

2019 ◽  
Author(s):  
Golan Karvat ◽  
Artur Schneider ◽  
Mansour Alyahyaey ◽  
Florian Steenbergen ◽  
Ilka Diester
Keyword(s):  
Real Time ◽  
Neurofeedback Training ◽  
Time Data ◽  
Beta Band ◽  
Neural Oscillation ◽  
Oscillatory Power ◽  
Analysis System ◽  
Data Analysis System ◽  
Induced Changes

AbstractNeural oscillations are increasingly interpreted as transient bursts, yet a method to measure these short-lived events in real-time is missing. Here we present a real-time data analysis system, capable to detect short and narrowband bursts, and demonstrate its usefulness for volitional increase of beta-band burst-rate in rats. This neurofeedback-training induced changes in overall oscillatory power, and bursts could be decoded from the movement of the rats, thus enabling future investigation of the role of oscillatory bursts.

scholarly journals Implementasi Web Service untuk Aplikasi Pemantau Coronavirus Disease 2019 (COVID-19)

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Faisal Al Isfahani ◽  
Fuji Nugraha ◽  
Rifki Mubarok ◽  
Alam Rahmatulloh
Keyword(s):  
Web Service ◽  
Real Time ◽  
Data Exchange ◽  
Human Life ◽  
Time Data ◽  
Service Architecture ◽  
Representational State Transfer ◽  
State Transfer ◽  
Android Applications

The SARS-CoV-2 coronavirus outbreak, or commonly abbreviated as Covid-19, is currently almost paralyzing human life in various sectors. Compared to other coronaviruses such as SARS-Cov and MERS-Cov, Covid-19 spreads very quickly in multiple countries and regions. Also, the difficulty of information obtained accurately and in real-time for the community. The role of information technology is vital for the community in monitoring the coronavirus. This research utilizes web service technology to collect data and integrate services from various sources. The protocol and web service architecture used is representational state transfer (REST), with independent data exchange using the JSON format. Web service is made with node.js as well as android applications using an android studio. The results of this study have obtained a mobile-based android application that can present covid-19 data accurately and in real-time. Data recapitulation coronaviruses distribution from four service sources that have been integrated can display globally and locally in Indonesia.

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