Integrated approach to drilling dynamics challenges in the Browse Basin

The use of drilling dynamics measurements has traditionally focused on improving downhole tool reliability. This, however, is a limited scope and in recognition of this, drilling dynamics is approached as a process that starts early in the planning stage of a project and targets the performance of the complete drillstring. Failures or inefficiencies associated with drillstring dynamics continue to occur in spite of the sophistication of today's measurements, particularly in exploratory projects that extend the present drilling envelope. Several methodologies were integrated to address the challenges of drilling dynamics and overcome frequent failures observed on the initial exploratory work on the Browse Basin. A steep learning curve was achieved by accelerating the improvement cycle using advanced modelling techniques and obtaining optimum designs without the need of multiple trial and error cycles. This extended abstract also describes the use of real-time dynamics measurements to quantify the risks related to drillstring vibration, a critical need for the drilling environment observed in the basin that ties planning work into the execution stage. Finally, the project cycle is closed with the evaluation of drilling performance using data-handling tools that allow the effective use of large amounts of drilling data generated during the execution and feedback into a new planning cycle. The extended abstract describes the implementation of drilling dynamics modelling to assist performance improvement, but more importantly, the methodology to incorporate it into a real-time decision-making process that maximises the value of technology implementation.

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An Integrated and Digitalized Approach to Reduce the Well Failure Index During Covid-19 Global Pandemic in Shushufindi Field

10.2118/208028-ms ◽

2021 ◽

Author(s):

Oki Maulidani ◽

Pedro Escalona ◽

Monica Paredes ◽

Maria Sierra ◽

Christian Bonilla ◽

...

Keyword(s):

Real Time ◽

Technology Implementation ◽

Global Economy ◽

New Technologies ◽

New Technology ◽

Integrated Approach ◽

Production Test ◽

Gas Industry ◽

Failure Index ◽

Big Picture

Abstract The Covid-19 pandemic is an unprecedented condition to the global economy including the oil & gas industry. The ability to adapt to the imposed changes, requires creativity, innovation, digitalization of processes, and resilience. This work will show a novel integrated approach around four pillars which had improved operation efficiency and brought monetary value during a challenging 2020 in Shushufindi field, Ecuador. The first pillar is new technology adoption. This aims to extend run life of critical equipment resulting in a higher well productive time. Examples of adopted technology: Chrome-enrich tubulars, downhole microcaps chemical deployment, de-sander and multiphase/extended gas handler. The second pillar is the P3 process (Pre-Pulling-Post) to quickly and effectively find the root cause of well failure that leads to definite remedial action. Digital enabler is the third pillar, its value come from reducing operational downtime and risk by using real-time surveillance capability, remote control, and data intelligence. The final pillar is to re-establish an effective communication with all stakeholders. Various dashboards have been developed in order to provide the big picture of actual field condition in quickly manner as well as implementation of ESP real time surveillance & diagnostics, real time multiphase production test, and chemical treatment automation. Workshops, online technical, and service quality meetings are regularly conducted to ensure that recommendations and opportunities can be executed properly including contractual negotiations to enable new technology implementation. Despite all the restrictions during covid-19 pandemic and some force majeures in 2020, this integrated and digitalized approach has resulted an outstanding outcome: Well failure index reduced from 0.62 in 2019 to 0.41 in 2020; Production deferment related to well failure declined significantly from 2,420 bopd in 2019 to 1,259 bopd in 2020, which translate in savings of $16.8 million dollars. In addition to that, there was a reduction on operational cost from $26.3 million dollars in 2019 to $15.2 million dollars in 2020. This proven initiative has been supported and recognized by all stakeholders. Some new technologies and digitalization projects are in the process to be implemented in Shushufindi field as part of Ecuador digital strategy 2022. This successful integrated and digitalized approach can be adopted in other fields and will generate a huge business impact.

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INTEGRATED APPROACH TO THE EFFECTIVE PROVISION OF HIGHER EDUCATION EDUCATIONAL PROGRAMS WITH LIBRARY AND INFORMATION RESOURCES

Scholarly Research and Information ◽

10.24108/2658-3143-2019-2-1-41-52 ◽

2019 ◽

Vol 2 (1) ◽

pp. 41-52 ◽

Cited By ~ 1

Author(s):

N. N. Kvelidze-Kuznetsova ◽

S. A. Morozova

Keyword(s):

Higher Education ◽

Integrated Approach ◽

Educational Programs ◽

Educational Process ◽

Educational Institutions ◽

Current State ◽

Software Product ◽

Using Data ◽

Types Of Information ◽

Effective Use

Educational and methodological support of the main professional educational programs of higher education (hereinafter referred to as MPEP) is an integral component and an important condition for the licensing, implementation and accreditation of these programs. An analysis of the publications of the last five years shows that universities and libraries of educational institutions are in search of modern software alternatives to the book supply modules included in automated library information systems (hereinafter — ABIS). In Herzen Stage Pedagogical University the launch of the Book Supply module, created as an external online software product using data streams from various sources, was the impetus for the formation of a whole complex of automated modules that allow real-time monitoring of the effective use in the educational process of both the printed fund and the fund of electronic publications presented on the platforms of publishers and aggregators, access to which is provided by subscription. Based on the data provided by the software package, the authors show the need and importance of continuous monitoring of the state of educational and methodological support of the educational process in order to respond quickly, adjust printed and electronic funds, interact meaningfully with departments and maintain the balance of printed and electronic information appropriate to the current state of development information technology and user readiness to perceive different types of information. The technique presented by the authors allows to form a harmonious content of educational and methodological support.

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Supplemental Material for Interdyad Differences in Early Mother–Infant Face-to-Face Communication: Real-Time Dynamics and Developmental Pathways

Developmental Psychology ◽

10.1037/a0032268.supp ◽

2013 ◽

Keyword(s):

Real Time ◽

Developmental Pathways ◽

Time Dynamics ◽

Face To Face

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A Prototype Quantitative Precipitation Estimation Algorithm for Operational S-Band Polarimetric Radar Utilizing Specific Attenuation and Specific Differential Phase. Part II: Performance Verification and Case Study Analysis

Journal of Hydrometeorology ◽

10.1175/jhm-d-18-0070.1 ◽

2019 ◽

Vol 20 (5) ◽

pp. 999-1014 ◽

Cited By ~ 9

Author(s):

Stephen B. Cocks ◽

Lin Tang ◽

Pengfei Zhang ◽

Alexander Ryzhkov ◽

Brian Kaney ◽

...

Keyword(s):

Real Time ◽

Heavy Precipitation ◽

Estimation Algorithm ◽

Differential Phase ◽

Specific Attenuation ◽

Quantitative Precipitation Estimation ◽

Precipitation Estimation ◽

Bias Ratio ◽

Using Data ◽

Precipitation Events

Abstract The quantitative precipitation estimate (QPE) algorithm developed and described in Part I was validated using data collected from 33 Weather Surveillance Radar 1988-Doppler (WSR-88D) radars on 37 calendar days east of the Rocky Mountains. A key physical parameter to the algorithm is the parameter alpha α, defined as the ratio of specific attenuation A to specific differential phase KDP. Examination of a significant sample of tropical and continental precipitation events indicated that α was sensitive to changes in drop size distribution and exhibited lower (higher) values when there were lower (higher) concentrations of larger (smaller) rain drops. As part of the performance assessment, the prototype algorithm generated QPEs utilizing a real-time estimated and a fixed α were created and evaluated. The results clearly indicated ~26% lower errors and a 26% better bias ratio with the QPE utilizing a real-time estimated α as opposed to using a fixed value as was done in previous studies. Comparisons between the QPE utilizing a real-time estimated α and the operational dual-polarization (dual-pol) QPE used on the WSR-88D radar network showed the former exhibited ~22% lower errors, 7% less bias, and 5% higher correlation coefficient when compared to quality controlled gauge totals. The new QPE also provided much better estimates for moderate to heavy precipitation events and performed better in regions of partial beam blockage than the operational dual-pol QPE.

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Modeling Fused Filament Fabrication using Artificial Neural Networks

Production Engineering ◽

10.1007/s11740-021-01020-y ◽

2021 ◽

Author(s):

Paul Oehlmann ◽

Paul Osswald ◽

Juan Camilo Blanco ◽

Martin Friedrich ◽

Dominik Rietzel ◽

...

Keyword(s):

Real Time ◽

Large Scale ◽

Cost Effective ◽

Print Quality ◽

Ann Model ◽

Production Environment ◽

Fused Filament Fabrication ◽

Artificial Neural ◽

Using Data ◽

Artificial Neural Network Ann

AbstractWith industries pushing towards digitalized production, adaption to expectations and increasing requirements for modern applications, has brought additive manufacturing (AM) to the forefront of Industry 4.0. In fact, AM is a main accelerator for digital production with its possibilities in structural design, such as topology optimization, production flexibility, customization, product development, to name a few. Fused Filament Fabrication (FFF) is a widespread and practical tool for rapid prototyping that also demonstrates the importance of AM technologies through its accessibility to the general public by creating cost effective desktop solutions. An increasing integration of systems in an intelligent production environment also enables the generation of large-scale data to be used for process monitoring and process control. Deep learning as a form of artificial intelligence (AI) and more specifically, a method of machine learning (ML) is ideal for handling big data. This study uses a trained artificial neural network (ANN) model as a digital shadow to predict the force within the nozzle of an FFF printer using filament speed and nozzle temperatures as input data. After the ANN model was tested using data from a theoretical model it was implemented to predict the behavior using real-time printer data. For this purpose, an FFF printer was equipped with sensors that collect real time printer data during the printing process. The ANN model reflected the kinematics of melting and flow predicted by models currently available for various speeds of printing. The model allows for a deeper understanding of the influencing process parameters which ultimately results in the determination of the optimum combination of process speed and print quality.

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Deep transient testing methodology: An integrated approach to redefine the real-time reservoir complexities and well deliverability

Journal of Petroleum Science and Engineering ◽

10.1016/j.petrol.2021.109179 ◽

2021 ◽

pp. 109179

Author(s):

Arvind Kumar ◽

Archana Balikram ◽

Keka Ojha

Keyword(s):

Real Time ◽

Integrated Approach ◽

The Real ◽

Testing Methodology

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An integrated approach to real-time system design and on-line performance visualization with steering

Proceedings 21st IEEE Real-Time Systems Symposium ◽

10.1109/real.2000.896004 ◽

2002 ◽

Author(s):

A.M. Bakic ◽

M.W. Mutka

Keyword(s):

System Design ◽

Real Time ◽

Integrated Approach ◽

Time System ◽

Real Time System ◽

Performance Visualization ◽

On Line

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Application of Real-Time Field Data to Optimize Drilling Hydraulics Using Neural Network Approach

Journal of Energy Resources Technology ◽

10.1115/1.4030847 ◽

2015 ◽

Vol 137 (6) ◽

Cited By ~ 31

Author(s):

Yanfang Wang ◽

Saeed Salehi

Keyword(s):

Neural Network ◽

Real Time ◽

Field Data ◽

Ann Model ◽

Time Data ◽

Neural Network Approach ◽

Lost Circulation ◽

Drilling Performance ◽

Artificial Neural Network Ann ◽

Pump Pressure

Real-time drilling optimization improves drilling performance by providing early warnings in operation Mud hydraulics is a key aspect of drilling that can be optimized by access to real-time data. Different from the investigated references, reliable prediction of pump pressure provides an early warning of circulation problems, washout, lost circulation, underground blowout, and kicks. This will help the driller to make necessary corrections to mitigate potential problems. In this study, an artificial neural network (ANN) model to predict hydraulics was implemented through the fitting tool of matlab. Following the determination of the optimum model, the sensitivity analysis of input parameters on the created model was investigated by using forward regression method. Next, the remaining data from the selected well samples was applied for simulation to verify the quality of the developed model. The novelty is this paper is validation of computer models with actual field data collected from an operator in LA. The simulation result was promising as compared with collected field data. This model can accurately predict pump pressure versus depth in analogous formations. The result of this work shows the potential of the approach developed in this work based on NN models for predicting real-time drilling hydraulics.

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