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‘Round-the-room’ introductions and review of seminar objectives
Today’s full field development entails the design of numerous subsea pipelines. This involves the execution of many calculations, involving multiple load cases and sensitivities over several design cycles to converge towards an acceptable design. Most of such tasks are historically performed manually using various blocks of code or tools such as FEA, spreadsheets, scripts. Those are run in series, with varying degrees of automation, but rarely conceived to be tied together conveniently.
This paper presents spidev_api, a Python library purposely designed to support subsea pipeline design. It includes a structured data model setting a standard for variables name & format, together with commands to manipulate such data model. It comes with an expanding catalog of pipeline design applications that interacts with such data model, and a reporting & visualization toolkit that produces design reports in various file formats.
The paper expands upon the organizational model & tools that were put in place to develop such source code. It describes how the code is maintained and deployed as an in-house weblike service.
A summary of the results already achieved is presented, together with an insight into the opportunities that can now be envisaged using such approach.
Vincent Cocault-Duverger, Amandine Laye & Simon Grevet, Saipem SA
Industrial automation is a key method for improving quality and reducing cost used in many sectors. This paper presents processes and tools that allow automation of the pipeline engineering activities such as routing, mechanical design and span assessment. Flowcharts will be presented that show how the process of CTR generation, engineering design, reporting and the handover to the execute and operations phase have been automated. Use of standard CTR allows for efficient proposal generation and the use of standard design deliverable lists. Use of a single database provides a single source of truth to drive the engineering design and is linked automatically to validated engineering calculations and analysis modules. The results are exported to a set of design deliverables which can be accessed by via a secure portal by all projects stakeholders. The output includes a summary of the code compliance and the margin of safety of each component. The design deliverables are output in a standard electronic format suitable for use during the procurement of long lead items and tendering of fabrication and installations activities. The design deliverables are revision controlled and can be updated as the design evolves or with as built information ready for the hand over to operations. This approach lets the engineers focus on design optimisation and value improvement.
Author: Colin McKinnon, Wood and Co Authors: Rob Kennedy, Andrew Rathbone and Yousef Achercouk, Wood
The session will give an overview of McDermott’s Digital technology advancements in the field of Subsea, how they positively impact collaboration within the organization and our clients while delivering a unique value proposition to the subsea industry. From concept study to the as-built field, participants will gain insight into the way McDermott and their partners drive the Digital revolution to reach new depths.
In recent years due to lower oil prices, not only the capital expenditure (CAPEX) but also the operational cost (OPEX) need to be reduced significantly which is very much challenging for the oil and gas operators specially for deep-water and subsea pipeline system. Proper Integrity management and maintenance planning are the key factors for reducing operational cost. Due to advancement of the wireless sensor-based technology such as Internet of Things (IoT), it becomes easier to monitor the sensors data real-time either locally using edge computing or on cloud using cloud-computing. In this paper, we will show that only IoT is not enough to monitor the sensor data as it also requires capability to take the decision based on outcome of the processed data. Here comes cognitive IoT, to make smarter IoT system with high-level intelligence like machine learning based on human cognition to handle massive data analytics and make intelligent decision making for maintenance. Cognitive IoT aggregates and process the sensor data from hundreds of different sensors (pressure, temperature, strain etc.) installed on subsea pipes and subsea systems. In this paper we will demonstrate a cognitive IoT system for subsea pipelines with simulated data (in absence of actual sensor data) to predict the maintenance requirement if necessary to avoid any sudden system broke down. This cognitive-IoT will save millions in OPEX cost by avoiding any sudden failure and subsequent shut down of whole system for maintenance.
Authors: Dr. Subrata Bhowmik, McDermott - Duncan McLachlan, IO Oil Gas (JV of McDermott & GE Oil & Gas) - Bharat Kumar Maryada, McDermott
Fatigue is an ever-present concern within the offshore environment, particularly when considering the operational integrity of slender structures such as flexible or steel risers, tension leg tendons or mooring systems. The current approach tends to adopt a combination of complex theoretical modelling and periodic risk-based inspection. The system under discussion uses an Artificial Neural Network approach to integrate data from these approaches building a virtual model which uses an asset’s existing hardware as the key system input, providing real time fatigue data as an output. We believe that this system offers a step change in operational integrity allowing operators to assess system performance in real time.