Integrated pre-drill and real-time geomechanical modelling brings significant benefits to deepwater wildcat exploration drilling campaign – a case study

2017 ◽  
Vol 57 (2) ◽  
pp. 698
Author(s):  
M. Sadegh Asadi ◽  
Amitava Ghosh ◽  
Sanjeev Bordoloi ◽  
Michael Reese
Keyword(s):  
Real Time ◽  
Wellbore Stability ◽  
Model Parameters ◽  
Seismic Velocities ◽  
Real Time Monitoring ◽  
Case Scenario ◽  
Worst Case ◽  
Primary Input ◽  
Exploratory Wells

This case study demonstrates the significance of integrated pre-drill geomechanical modelling and real-time monitoring for drilling wildcat exploratory wells in the deepwater settings of an offshore field in South-East Asia. The key challenges in the area include deeper water depths (1.6 km), lack of relevant offset well information and a complex geological setting. In this project, the primary input data for the pre-drill geomechanical model were low resolution 2D seismic velocities derived from an un-calibrated velocity model and petrophysical data from an offset well located in shallow waters, 100 km away from the deepwater prospect. During pre-drill planning, a contingency casing plan was put in place to consider the uncertainties in the model and cover the worst-case scenario of high pore pressure (PP). To reduce the uncertainty during drilling, the well was monitored in real-time and the pre-drill predictions improved whenever new information or data became available. The objective was to have good data coverage to assist in real-time geomechanical modelling for operational decision making. Real-time wellbore stability monitoring was carried out by utilising all available drilling and logging data as well as logging while drilling (LWD), pressure measurements and seismic while drilling (SWD) velocities. Wellsite interpretation on cuttings, cavings and formation gases were also integrated into the model predictions. Based on real-time monitoring, pre-drill predictions and model parameters were continuously updated for the next planned section at the end of each section target depth (TD). Interactive real-time monitoring with continuous pre-drill model updates before drilling the subsequent sections helped to not only deepen the intermediate hole sections, but also to drill efficiently with proper mud weight management and without any significant wellbore instability issues. This integrated workflow helped to successfully drill two exploratory wells, with the major benefit of eliminating the contingency 6ʹʹ slim-hole section.

Dynamic Data-Driven Spatiotemporal System Behavior Prediction With Simulations and Sensor Measurement Data

2018 ◽  
Author(s):  
Xiangxue Zhao ◽  
Shapour Azarm ◽  
Balakumar Balachandran
Keyword(s):  
Dynamical System ◽  
Real Time ◽  
Measurement Data ◽  
Data Driven ◽  
Sensor Data ◽  
Model Parameters ◽  
High Fidelity ◽  
System Behavior ◽  
Sensor Measurement

Online prediction of dynamical system behavior based on a combination of simulation data and sensor measurement data has numerous applications. Examples include predicting safe flight configurations, forecasting storms and wildfire spread, estimating railway track and pipeline health conditions. In such applications, high-fidelity simulations may be used to accurately predict a system’s dynamical behavior offline (“non-real time”). However, due to the computational expense, these simulations have limited usage for online (“real-time”) prediction of a system’s behavior. To remedy this, one possible approach is to allocate a significant portion of the computational effort to obtain data through offline simulations. The obtained offline data can then be combined with online sensor measurements for online estimation of the system’s behavior with comparable accuracy as the off-line, high-fidelity simulation. The main contribution of this paper is in the construction of a fast data-driven spatiotemporal prediction framework that can be used to estimate general parametric dynamical system behavior. This is achieved through three steps. First, high-order singular value decomposition is applied to map high-dimensional offline simulation datasets into a subspace. Second, Gaussian processes are constructed to approximate model parameters in the subspace. Finally, reduced-order particle filtering is used to assimilate sparsely located sensor data to further improve the prediction. The effectiveness of the proposed approach is demonstrated through a case study. In this case study, aeroelastic response data obtained for an aircraft through simulations is integrated with measurement data obtained from a few sparsely located sensors. Through this case study, the authors show that along with dynamic enhancement of the state estimates, one can also realize a reduction in uncertainty of the estimates.

scholarly journals Near real-time monitoring of HIV transmission hotspots from routine HIV genotyping: an implementation case study

2016 ◽  
Vol 3 (5) ◽  
pp. e231-e238 ◽  
Author(s):  
Art F Y Poon ◽  
Réka Gustafson ◽  
Patricia Daly ◽  
Laura Zerr ◽  
S Ellen Demlow ◽  
...  
Keyword(s):  
Real Time ◽  
Hiv Transmission ◽  
Real Time Monitoring

Evaluation of a Connectionless Technique for System-on-Chip Interconnection

2016 ◽  
Vol 25 (10) ◽  
pp. 1630005 ◽  
Author(s):  
Marcelo Daniel Berejuck ◽  
Antônio A. Fröhlich
Keyword(s):  
Real Time ◽  
High Performance ◽  
Communication Channel ◽  
Resource Reservation ◽  
Multimedia Applications ◽  
Worst Case ◽  
Average Latency ◽  
On Chip ◽  
Hard Real Time

We present the design and evaluation of a high-performance network-on-chip (NoC) focused on telecommunication and multimedia applications that tolerate latency and bandwidth variations. The design is based on a connectionless strategy in which flits from different communication flows are interleaved in the same communication channel. Each flit carries routing information that is used by routers to perform arbitration and scheduling of the corresponding output ports in order to balance channel utilization. In order to compare our approach with others, we introduce an analytic model for the worst-case latency (WCL) of our NoC and recall those of related approaches. Analytic comparisons and experimental data show that our approach keeps average WCL lower for variable-bit-rate multimedia applications than a network based on resource reservation. For these applications, the overall throughput is larger than that of networks that perform resource reservation. A case study based on the proposed NoC shows that the average latency was 28% lower than the WCL expected for the experiment. Indeed, hard real-time flows designed considering the absolute WCL of the network will always meet the requirements of the associated hard real-time tasks, so no deadline can be lost due to network contention.

scholarly journals Deformations on the ship sections during fabrication: cause and remedies

2021 ◽  
Vol 44 ◽  
pp. 15-22
Author(s):  
Eisawy Mohamed ◽  
Renardo-Florin Teodor
Keyword(s):  
Production Cost ◽  
Deformation Characteristics ◽  
The Finite Element Method ◽  
Case Scenario ◽  
Worst Case ◽  
Turning Operations ◽  
Influencing Parameters ◽  
Steel Cutting ◽  
Process Material

During fabrication process, material deformations are likely to occur due to various factors such as heat during steel cutting, welding induced deformations, lifting and turning of ship sections, temporary stiffening and other possible modifications of ship sections. Lifting induced deformations is one of the major causes of deformations that highly affect the production cost and quality. The aim of this thesis is to outline the main causes of deformations that occur in ship sections during fabrication and to analyse in detail the lifting and turning operations of one ship section using the Finite Element Method (FEM). A strength check using the FEM has been performed on the selected ship section to investigate the deformations and stresses in two different cases with three different loading conditions. First, the section has been analysed without temporary stiffening in three load scenarios: lifting before turning, worst-case scenario during turning and lifting after turning. Similarly, the second case study has been analysed but with the temporary stiffening added according to the lifting plan. Various influencing parameters that determine the lifting plan has been investigated such as the sling angle which directly affects the deformation characteristics. It is observed that the addition of temporary stiffening is essential to minimize the deformations and to maintain the stress levels below the yield point.

Smart Segmented Polymer Injection Pilot: A Case Study

2021 ◽  
Author(s):  
Fuchao Sun ◽  
Xiaohan Pei ◽  
Xubo Gai ◽  
Shuang Sun ◽  
Shifeng Hu
Keyword(s):  
Real Time ◽  
Pressure Sensors ◽  
Adjustment Process ◽  
Injection Technique ◽  
Control Line ◽  
Real Time Monitoring ◽  
Time Data ◽  
Polymer Injection ◽  
Polymer Flood

Abstract Polymer flood is proved an effective method for EOR in China. Traditional segmented polymer injection technique cannot obtain continuous layer parameters. Real-time monitoring is necessary for polymer flood because downhole pressure and flowrate vary more often than waterflood. Existing technique for layered monitoring and flowrate adjustment is wireline test. There is no smart technique which can realize real-time monitoring and automatic flowrate control. In this paper, a smart segmented injection technique for polymer flood well is introduced. A smart distributor is permanently placed in each layer. It is composed of flowmeter, temperature sensor, two pressure sensors, downhole choke and electrical control unit. The special flowmeter is adopted for polymer flowrate test. All the distributors are connected together by a single control line which is set outside of the tubing string. Operator can read the data of each layer and adjust the flowrate whenever needed at any time which makes the technique a smart one. The smart technique for polymer flood wells has been implemented in a polymer well in Daqing oilfield of China. A case study for smart segmented polymer injection pilot is introduced in detail including technical principle, indoor test results, construction process and adjustment process. The application results show that the operator on the ground can easily obtain downhole tubing pressure, layer annulus pressure, temperature and flowrate on line. The sample time can be set to any one between 1-65536s according to geological engineer's advice. There is no limitation caused by battery power because the distributor is powered by cable on the ground. In terms of adjustment, the flowrate can be adjusted according to the target value. And it can also be regulated at any time manually, just needing pushing the mouse in the office. The application also displays that the smart segmented technique has the advantage for polymer injection because of larger change of layered parameters. It can provide more real-time data for oil development engineer and the data are beneficial for better understanding and optimization of the reservoir. Therefore, the smart segmented polymer injection has a great potential for EOR based on polymer flood.

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