Fault characterization and flow barrier detection using capacitance-resistance model and diagnostic plots

2021 ◽  
pp. 109817
Author(s):  
Oscar I.O. Ogali ◽  
Oyinkepreye D. Orodu
Keyword(s):  
Diagnostic Plots ◽  
Resistance Model ◽  
Fault Characterization

Kajian Kinerja Kapal Bantu Hidro-Oceanography

2019 ◽  
Vol 4 (1) ◽  
pp. 35
Author(s):  
Meitha Soetardjo ◽  
Dian Purnamasari
Keyword(s):  
Preliminary Design ◽  
Resistance Model ◽  
Supporting Force

Bantu Hidro-Oceanography (BHO) adalah salah satu satuan bantu dalam bidang survei Hidro-Oceanography yang termasuk dalam susunan tempur pendukung (Supporting Force). Untuk kepentingan tersebut maka preliminary design kapal Hidro-Oceanography dilaksanakan sebagai langkah awal dalam perencanaan dan pengadaan kapal Hidro-Oceanography untuk mengkaji karakteristik umum desain yaitu hidrostatik dan stabilitas sehingga aspek kelayakan kapal dapat terpenuhi. Analisa hasil kajian kinerja kapal Hidro-Oceanography dipersiapkan untuk pengujian tahanan/resistance model kapal.Keywords : Preliminary design1, Hydrostatic2, Stability3

scholarly journals Thermal-wet model of knitted double jersey based on backpropagation algorithm of neural network

2020 ◽  
Vol 15 ◽  
pp. 155892501990083
Author(s):  
Xintong Li ◽  
Honglian Cong ◽  
Zhe Gao ◽  
Zhijia Dong
Keyword(s):  
Neural Network ◽  
Water Vapor ◽  
Thermal Resistance ◽  
Resistance Test ◽  
Training Algorithm ◽  
Backpropagation Algorithm ◽  
Optimal Network ◽  
Resistance Model ◽  
Hidden Layer ◽  
The Relationship

In this article, thermal resistance test and water vapor resistance test were experimented to obtain data of heat and humidity performance. Canonical correlation analysis was used on determining influence of basic fabric parameters on heat and humidity performance. Thermal resistance model and water vapor resistance model were established with a three-layered feedforward-type neural network. For the generalization of the network and the difficulty of determining the optimal network structure, trainbr was chosen as training algorithm to find the relationship between input factors and output data. After training and verification, the number of hidden layer neurons in the thermal resistance model was 12, and the error reached 10−3. In the water vapor resistance model, the number of hidden layer neurons was 10, and the error reached 10−3.

Fault characterization and modelling in the Deep Mill Level Zone (DMLZ) mine

2020 ◽  
Author(s):  
Dhani Haflil ◽  
S Widodo ◽  
P Wiguna ◽  
Wayne Barnett ◽  
Luca Zorzi ◽  
...  
Keyword(s):  
Fault Characterization

Diagnostic Plots for Production Decline During the Transition of Oil Field Development From Depletion to Water Injection

2021 ◽  
Author(s):  
Vil Syrtlanov ◽  
Yury Golovatskiy ◽  
Ivan Ishimov
Keyword(s):  
Water Injection ◽  
Simulation Models ◽  
Oil Field ◽  
Production Data ◽  
Oil Reservoir ◽  
Field Development ◽  
Well Production ◽  
Diagnostic Plots ◽  
Oil Field Development ◽  
Analytical Approaches

Abstract In this paper the simplified way is proposed for predicting the dynamics of liquid production and estimating the parameters of the oil reservoir using diagnostic curves, which are a generalization of analytical approaches, partially compared with the results of calculations on 3D simulation models and with actual well production data.

The Co2crc Otway Shallow Co2 Controlled Release Experiment: Fault Characterization and Leakage Scenarios

2021 ◽  
Author(s):  
Andrew Feitz ◽  
Bruce Radke ◽  
Kwong Soon Chan ◽  
Ludovic Ricard ◽  
Aleks Kalinowski ◽  
...  
Keyword(s):  
Controlled Release ◽  
Release Experiment ◽  
Fault Characterization

Application of Multiple Diagnostic Plots to Identify End of Linear Flow in Unconventional Reservoirs

2021 ◽  
Author(s):  
Helmi Pratikno ◽  
W. John Lee ◽  
Cesario K. Torres
Keyword(s):  
Material Balance ◽  
Unconventional Reservoirs ◽  
Production Data ◽  
Reservoir Properties ◽  
Type Curve ◽  
Linear Flow ◽  
Diagnostic Plots ◽  
Actual Time ◽  
Rate Versus ◽  
Public Data

Abstract This paper presents a method to identify switch time from end of linear flow (telf) to transition or boundary-dominated flow (BDF) by utilizing multiple diagnostic plots including a Modified Fetkovich type curve (Eleiott et al. 2019). In this study, we analyzed publicly available production data to analyze transient linear flow behavior and boundary-dominated flow from multiple unconventional reservoirs. This method applies a log-log plot of rate versus time combined with a log-log plot of rate versus material balance time (MBT). In addition to log-log plots, a specialized plot of rate versus square root of time is used to confirm telf. A plot of MBT versus actual time, t, is provided to convert material balance time to actual time, and vice versa. The Modified Fetkovich type curve is used to estimate decline parameters and reservoir properties. Applications of this method using monthly production data from Bakken and Permian Shale areas are presented in this work. Utilizing public data, our comprehensive review of approximately 800 multi-staged fractured horizontal wells (MFHW) from North American unconventional reservoirs found many of them exhibiting linear flow production characteristics. To identify end of linear flow, a log-log plot of rate versus time alone is not sufficient, especially when a well is not operated in a consistent manner. This paper shows using additional diagnostic plots such as rate versus MBT and specialized plots can assist interpreters to better identify end of linear flow. With the end of linear flow determined for these wells, the interpreter can use the telf to forecast future production and estimate reservoir properties using the modified type curve. These diagnostic plots can be added to existing production analysis tools so that engineers can analyze changes in flow regimes in a timely manner, have better understanding of how to forecast their wells, and reduce the uncertainty in estimated ultimate recoveries related to decline parameters.

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