Real Time Fracture Placement and Completion Design Using an Azimuthal LWD Sonic and Spectral Gamma Ray Analysis for an Anisotropic Unconventional Reservoir Evaluation

2014 ◽  
Author(s):  
Claudia Amorocho ◽  
Cory Langford ◽  
Camilo Mejia
Keyword(s):  
Real Time ◽  
Gamma Ray ◽  
Unconventional Reservoir ◽  
Reservoir Evaluation

Real-time signal processing in field programmable gate array based digital gamma-ray spectrometer

2020 ◽  
Vol 91 (10) ◽  
pp. 104707
Author(s):  
Yinyu Liu ◽  
Hao Xiong ◽  
Chunhui Dong ◽  
Chaoyang Zhao ◽  
Quanfeng Zhou ◽  
...  
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Field Programmable Gate Array ◽  
Gamma Ray ◽  
Time Signal ◽  
Gamma Ray Spectrometer ◽  
Field Programmable ◽  
Gate Array ◽  
Real Time Signal Processing

scholarly journals Neutrino Astronomy with IceCube

2016 ◽  
Vol 12 (S324) ◽  
pp. 322-329
Author(s):  
Kevin J. Meagher
Keyword(s):  
Real Time ◽  
Gamma Ray ◽  
Galactic Plane ◽  
Galactic Nuclei ◽  
High Energy ◽  
Glacial Ice ◽  
Astrophysical Neutrinos ◽  
Charged Secondary ◽  
Neutrino Astronomy ◽  
The Antarctic

AbstractThe IceCube Neutrino Observatory is a cubic kilometer neutrino telescope located at the Geographic South Pole. Cherenkov radiation emitted by charged secondary particles from neutrino interactions is observed by IceCube using an array of 5160 photomultiplier tubes embedded between a depth of 1.5 km to 2.5 km in the Antarctic glacial ice. The detection of astrophysical neutrinos is a primary goal of IceCube and has now been realized with the discovery of a diffuse, high-energy flux consisting of neutrino events from tens of TeV up to several PeV. Many analyses have been performed to identify the source of these neutrinos: correlations with active galactic nuclei, gamma-ray bursts, and the galactic plane. IceCube also conducts multi-messenger campaigns to alert other observatories of possible neutrino transients in real-time. However, the source of these neutrinos remains elusive as no corresponding electromagnetic counterparts have been identified. This proceeding will give an overview of the detection principles of IceCube, the properties of the observed astrophysical neutrinos, the search for corresponding sources (including real-time searches), and plans for a next-generation neutrino detector, IceCube–Gen2.

A Novel Workflow for Geosteering a Horizontal Well in a Low Resistivity Contrast Anisotropic Environment: A Case Study in Semoga Field, Indonesia

2021 ◽  
Author(s):  
Yessica Fransisca ◽  
Karinka Adiandra ◽  
Vinda Manurung ◽  
Laila Warkhaida ◽  
M. Aidil Arham ◽  
...  
Keyword(s):  
Real Time ◽  
Horizontal Well ◽  
Gamma Ray ◽  
Lessons Learned ◽  
Electrical Anisotropy ◽  
Anisotropy Ratio ◽  
Well Placement ◽  
Low Contrast ◽  
Low Resistivity ◽  
The Subject

Abstract This paper describes the combination of strategies deployed to optimize horizontal well placement in a 40 ft thick isotropic sand with very low resistivity contrast compared to an underlying anisotropic shale in Semoga field. These strategies were developed due to previously unsuccessful attempts to drill a horizontal well with multiple side-tracks that was finally drilled and completed as a high-inclined well. To maximize reservoir contact of the subject horizontal well, a new methodology on well placement was developed by applying lessons learned, taking into account the additional challenges within this well. The first approach was to conduct a thorough analysis on the previous inclined well to evaluate each formation layer’s anisotropy ratio to be used in an effective geosteering model that could better simulate the real time environment. Correct selections of geosteering tools based on comprehensive pre-well modelling was considered to ensure on-target landing section to facilitate an effective lateral section. A comprehensive geosteering pre-well model was constructed to guide real-time operations. In the subject horizontal well, landing strategy was analysed in four stages of anisotropy ratio. The lateral section strategy focused on how to cater for the expected fault and maintain the trajectory to maximize reservoir exposure. Execution of the geosteering operations resulted in 100% reservoir contact. By monitoring the behaviour of shale anisotropy ratio from resistivity measurements and gamma ray at-bit data while drilling, the subject well was precisely landed at 11.5 ft TVD below the top of target sand. In the lateral section, wellbore trajectory intersected two faults exhibiting greater associated throw compared to the seismic estimate. Resistivity geo-signal and azimuthal resistivity responses were used to maintain the wellbore attitude inside the target reservoir. In this case history well with a low resistivity contrast environment, this methodology successfully enabled efficient operations to land the well precisely at the target with minimum borehole tortuosity. This was achieved by reducing geological uncertainty due to anomalous resistivity data responding to shale electrical anisotropy. Recognition of these electromagnetic resistivity values also played an important role in identifying the overlain anisotropic shale layer, hence avoiding reservoir exit. This workflow also helped in benchmarking future horizontal well placement operations in Semoga Field. Technical Categories: Geosteering and Well Placement, Reservoir Engineering, Low resistivity Low Contrast Reservoir Evaluation, Real-Time Operations, Case Studies

scholarly journals Handheld real-time volumetric 3-D gamma-ray imaging

2017 ◽  
Vol 857 ◽  
pp. 42-49 ◽  
Author(s):  
Andrew Haefner ◽  
Ross Barnowski ◽  
Paul Luke ◽  
Mark Amman ◽  
Kai Vetter
Keyword(s):  
Real Time ◽  
Gamma Ray ◽  
Gamma Ray Imaging

Coal identification using neural networks with real-time coalbed methane drilling data

2019 ◽  
Vol 59 (1) ◽  
pp. 319 ◽  
Author(s):  
Ruizhi Zhong ◽  
Raymond Johnson Jr ◽  
Zhongwei Chen ◽  
Nathaniel Chand
Keyword(s):  
Real Time ◽  
Coalbed Methane ◽  
Gamma Ray ◽  
Ann Model ◽  
Drilling Data ◽  
Weight On Bit ◽  
Net To Gross ◽  
Rotary Speed ◽  
Artificial Neural Network Ann ◽  
Log Interpretation

Currently, coal is identified using coring data or log interpretation. Coring is the most dependable methodology, but it is costly and its characterisation is expensive and time consuming. Logging methods are convenient, reliable, and reproducible, but can be subject to statistical and shouldering effects and often have operational difficulties in deviated or horizontal wells. Drilling data, which are routinely available, can potentially be used to identify coal sections in a machine learning environment when conventional wireline logs are not available. To achieve this, a four-layer artificial neural network (ANN) was used to identify coals in a well at Walloon Sub-Group, Surat Basin. The ANN model used drilling data and some logging-while-drilling (LWD) data. The inputs for the lithological model from high-frequency drilling data include weight on bit, rotary speed, torque, and rate of penetration. Inputs from LWD data include gamma ray and hole diameter. The criterion for coal identification is based on bulk density cutoff. The simulation results show that the ANN can deliver an overall accuracy of 96%. Due to the low net-to-gross ratio of coals within the Walloon sequence, a lower but reasonable F1 score of 0.78 is achievable for the coal sections. The proposed model can potentially be implemented in real-time to identify coal intervals without additional logs and aid validation of minimal log data.

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