bluuebunny/crossref_metadata_2025_split huggingface dataset:
Building The World’S First Offshore All-membrane Water Injection Plant
Authors: Orr Graeme , Rajkovic Tanja 
Published: April 2020

Abstract

Objectives/Scope
The objective of this paper is to describe the process technology and construction of the world's first seawater sulphate removal plant using membranes for the key treatment stages.

Methods, Procedures, Process
SUEZ and Techouse have jointly developed the water injection module for the Equinor FPSO Johan Castberg. The vessel will be stationed in the Barents Sea, north of the Arctic Circle in 360-390m of water. The water injection capacity is specified by the client as 180,000 barrels per day with a sulphate content of &lt;40ppm and an oxygen content of &lt;20ppb. The environmental challenges of this location meant that a fresh design perspective was required to operate the water injection plant to this specification. NORSOK engineering standards are also required.
The traditional treatment process for this type of installation is pre-filtration by multi-media, cartridge filtration, nanofiltration membranes for sulphate removal, followed by vacuum tower deoxygenation. This paper will describe the alternative process solutions proposed, using an all-membrane process train and describe the benefits in terms of weight, footprint and operability, plus progress with construction to date.

Results, Observations, Conclusions
The water injection module is structurally complete as at September 2019 and is unique in that it is fully enclosed. Construction has been optimised by using the walls as a structural component rather than just cladding, thus keeping weight and structural complexity to a minimum.

Novel/Additive Information
Unique features of this plant are:
Ocean Bottom Node Seismic and Full Waveform Inversion Towards Better Imaging Over a Complex Sub-Salt Field in Deepwater Gulf of Mexico
Authors: Mohapatra Gopal Krishna , Martins Wisley , Checkles Steve , Duncan Gregory 
Published: April 2020

Abstract
The Stampede Field is a sub-salt Miocene field in the deepwater Gulf of Mexico. Although it is a generally well imaged structure, development and production requirements warranted an improved image over the field. A variety of seismic data such as Narrow Azimuth (NAz), Wide Azimuth (WAz), and Dual Coil (i.e., Full Azimuth or FAz) have been used at various stages in the past. Imaging the field is complicated by the presence of up to 15,000 ft of salt which includes overhangs, inclusions, sutures, steeply dipping flanks, and a rugose base. Successful imaging of the northwest portion of the field has consistently been a challenge, regardless of the vintage or technique used in acquisition and processing.
Recently, Ocean Bottom Nodes (OBN) seismic acquisition technology has become popular due to its long offset and low frequency content, which are essential to address complex imaging issues. In 2018, Hess engaged Fairfield Nodal to acquire OBN seismic over the Stampede Field, which recently started production. Acquisition design was based on an OBN modeling study. Nodes were placed over 238 sq km with shots over an 888 sq km area. The survey was safely executed without any incident or lost time. The data recovery was excellent. Data was processed with technologies including Full Waveform Inversion (FWI) for velocity model building and Least Squares Reverse-Time Migration (LSRTM). Dual coil and WAz data were used along with OBN to produce a superior image of the field.
In this paper, we will discuss (1) the logistics of node acquisition over a producing field with infrastructure on the seabed and rigs at work and (2) the image uplift from processing the data using cutting edge technologies like FWI and LSRTM.
The Re-Use of Offshore Wellhead Platform to Facilitate A Marginal Field Development – Vestigo Experience
Authors: Jamil Mohd Rashid , Mustapha Munira , Othman Muammar Gadafi 
Published: April 2020

This paper presents the successful delivery of Jitang Field Development project, a marginal field located offshore Peninsular Malaysia. Vestigo Petroleum Sdn Bhd (Vestigo), a wholly owned subsidiary of Petronas Carigali Sdn Bhd (PCSB) as operator of the field has set-up a new benchmark in Malaysia when Jitang field commenced production in January 2020:
The first in Malaysia to leverage on existing surface facilities via re-using/relocating Wellhead Platform (WHP)
Commenced production within 13 months from project's Final Investment Decision (FID)
Utilising suction pile technology and novel transport and installation (T&I) methodology to relocate the substructure and topsides of the WHP in a single piece from original to new location
Development of Jitang field consists of a WHP, an FPSO and a flowline evacuating full well stream from four wells. This paper will focus on WHP as the relocation of the WHP is the main feature and key driver of the project. Technical due diligence effort that was done in mitigating risks are also emphasized.
Vestigo's experience of re-using an existing WHP upon decommissioning the facility and re-installing it at a new location for re-use; proven that the concept works for effective solution of marginal field development. Jitang project has demonstrated significant improvement in project delivery schedule and cost saving.
A High-Resolution Regional Wave Resource Characterization for the U.S. West Coast
Authors: Wang Taiping , Yang Zhaoqing , Ticona Rollano Fadia Marion , Wu Wei-Cheng , García-Medina Gabriel 
Published: April 2020

AbstractObjectives/ScopeWave resource characterization is a critical step for wave energy converter deployment in the coastal ocean and relies on long-term, high-resolution wave datasets. This study presents a detailed modeling study of the wave resource along the U.S. West Coast (Washington, Oregon, and California), a coastal region that was identified with high wave energy potential in earlier studies.Methods, Procedures, ProcessThe wave hindcast covers a 32-year period from 1979 to 2010 and is based on a multi-resolution, unstructured-grid SWAN model framework. Model configuration closely follows and meets the requirements recommended by the International Electrotechnical Commission Technical Specification (IEC TS) for wave energy resource assessment and characterization (Class 2 - feasibility study). The model domain covers the entire U.S. Exclusive Economic Zone (EEZ) in the West Coast and has a spatial resolution varying from ~300 m in the nearshore region (20 km from the shoreline) to ~2500 m within the EEZ and ~5000 m at the open boundary, which extends beyond the EEZ. The model was forced by hourly 2-D wave spectra produced by a two-way nested WaveWatch III model, which covers the global ocean domain and the broader U.S. West Coast region domain with spatial resolutions of 0.5 degree and 10 arc-minutes, respectively. Both wave models are forced by hourly, 0.5-degree wind forcing obtained from NCEP's Climate Forecast System Reanalysis (CFSR) product.Results, Observations, ConclusionsThe standard model output for the SWAN model includes 3-hourly output for the six IEC wave resource parameters (e.g., omnidirectional wave power) at each grid point and hourly 2-D spectra at more than 50 NDBC buoys. Extensive model validation was achieved by comparing the six model-predicted IEC parameters with those derived from field observations at representative NDBC buoys. The error statistics indicated the model's satisfactory performance. Further analyses were conducted to systematically evaluate the temporal and spatial distributions of wave energy potential and wave climate along the U.S. West Coast. Results suggest that Washington and Oregon coasts have similar nearshore wave resource, which is significantly higher than resources in Southern California. Strong seasonal variations are also observed, e.g., high wave energy tends to occur in the winter months. In summary, this study produced the first high-resolution, comprehensive dataset on wave energy distribution along the U.S. West Coast.Novel/Additive InformationThe results are being used by the National Renewable Energy Laboratory to update the MHK Atlas, which was originally derived from NOAA's 4-arc-minute WaveWatch III model output. In addition, the monthly averaged wave energy climatology dataset can be readily shared to support a variety of research and application efforts within the EEZ of the U.S. West Coast.
Subsea Leak Detection Systems at Appomattox
Authors: Thompson Stephen Taylor , Bentsen Stian , Manfield Philip David 
Published: April 2020

The Appomattox asset, which currently has an expected production of 175,000 barrels of oil equivalent per day (boe/d), is a floating production system fed by several subsea production drill centers in the Gulf of Mexico, located in blocks MC437, 348, and 391-393. As the focus on in-situ leak detection has grown, two leak detection systems were implemented at Appomattox. Each uses an entirely different methodology for leak detection.
The Conditional Rate of Change (C-ROC) algorithm resides in the production control system and uses existing subsea pressure sensors. This algorithm was developed by Shell and is detailed in separate publications. Developed in parallel to the Appomattox project, C-ROC was added to the project later in the project lifecycle as it has become the Shell Gulf of Mexico standard for leak detection. In addition to the C-ROC method, each of the production drill centers has an Acoustic Leak Detector (ALD), provided by Naxys AS, a Baker Hughes business. These units are being piloted by Shell for the Gulf of Mexico. The ALD acoustically monitors the production manifold, wells, and associated flowline hardware at each drill center. The system is designed to distinguish the difference between background noise and actual leaks.
Implementation of each of these technologies leverage several other novel technologies and uses of existing technologies at Appomattox, including high bandwidth communications to support ALD and high-fidelity process simulation to both validate and train operations staff on the C-ROC algorithm.
This paper provides an overview of each leak detection system, details the technologies leveraged to implement these systems, and relates the project experiences thus far with each method.
Thermal Shock Transient Analysis for Well Integrity Through Operational Envelope
Authors: Agostini Cristiano Eduardo , Júnior Nelson Moreira , dos Santos Cleidilson Moura , Roman Roger Savoldi , Schnitzler Eduardo , Ferreira Marcus Vinicius Duarte , de Souza Charlton Okama , Weidlich Marcos Correa , Silva Alan Pinheiro 
Published: April 2020

Abstract
A physical evidence of an injector well failure caused by transient thermal behavior in cooling operations has lead to technical actions in order to provide a safe operational envelope. A modified thermal analysis was developed to predict the transient thermal behavior that can result in a cascade casing collapse. The as built approach was applied in a number of wells already constructed in a Brazilian offshore field resulting in a better way for selecting which mitigation method can be appropriate for each case. One of the main results from the study was to establish a controlled injection flow rate in order to avoid a cascade casing collapse due to thermal shock in the wellbore. In some cases, it was necessary to provide an annulus pressure communication in the wellhead using a ROV for bleeding off the excessive pressure in C annulus. With these actions, the wells studied were able to present a safe operational envelope. The approach commonly employed in the industry takes into account just steady state injection operations, which are not enough to describe what is happening in the field and also are not sufficient to support a suitable casing design. The industry must put efforts to develop and consolidate a methodology based on transient thermal analysis to deal with thermal shock events in the well, as proposed in this paper. Furthermore, this work also proposes four alternatives to mitigate the well integrity loss based on the transient thermal simulations and a comprehensive well risk assessement.
Increasing Facility Uptime Using Machine Learning and Physics-Based Hybrid Analytics in a Dynamic Digital Twin
Authors: Srikonda Rohit , Rastogi Ankur , Oestensen Haavard 
Published: April 2020

Abstract
The industry remains focused on achieving efficiency gains through accessing and processing production, asset and original equipment manufacturer (OEM) data, and applying machine learning (ML) principles to arrive at improved outcomes. As a service provider, we are experiencing an increased activity level related to hybrid analytics which involves embedding high-fidelity physics-based models together with ML models to improve outcomes. Critically, rather than addressing one piece of equipment, or a subset of a facility, companies focus on economies of scale, and seek asset-wide understanding of implications to equipment condition when changing operating parameters.
Deployment of a Dynamic Digital Twin provides production and maintenance engineers with a ‘single source of truth’ for information (i.e. P&ID, PFD, OEM information, maintenance history, etc.) integrated with high-fidelity physics-based models for subsea and topsides processes. Field sensors measuring hydrocarbon quantity, quality and other physical properties are integrated to provide real-time and historic data. Physics-based dynamic process models are first calibrated to match the field sensor data and then used to generate synthetic data for training ML models. A high-fidelity model generates virtual measurements where field sensors are not available. Access to such high-quality virtual measurements presents a paradigm shift for upstream analytics, as ML algorithms now have access to larger datasets for training. This improves quality, allowing for proactive planning and improved uptime leading to increased facility uptime by predicting equipment failure and enabling condition-based maintenance (CBM).
In our work with major oil and gas operators, we have observed that maintenance engineers until now have struggled, because enough field sensors are not always available to support the ML algorithms, leading to less specific assumptions and lower quality results. By taking advantage of a Dynamic Digital Twin - containing the asset structure, visualization and models - hybrid analytics were applied to continuously improve predictions, thereby increasing facility uptime.
In this paper, we present a few case studies of applying hybrid analytics with some oil and gas operators to enable virtual flow metering, prediction of unplanned equipment shutdown and prediction of optimum operating parameters for increased facility uptime. Examples presented demonstrate the integration of historic and real-time measurements with the physics-based process and multiphase flow models, and ML algorithms such as Autoencoder (AE), Long Short-term Memory (LSTM) neural networks and Reinforcement Learning.
Economic Feasibility Study of Several Utilization Alternatives For A Stranded Offshore Gas Reservoir
Authors: Trinh Khoi Viet , G. Moghanloo Rouzbeh Ghanbarnezhad 
Published: April 2020

Abstract
Floating Liquefied Natural Gas (FLNG) has been on the rise in recent years to meet growing energy demand, worldwide. As energy consumption and exploitation of onshore unconventional gas reservoirs continue to grow while gas price remains almost steady, FLNG can potentially become the key for operators in offshore gas fields through integration of upstream and midstream processes on the spot.
This paper compares project economics of a FLNG utilization to those of onshore LNG plant, and Gas-to-Wire (GTW) processes. Sensitivity analysis and tornado charts are used to evaluate importance of various uncertain parameters associated with FLNG construction and operation. Costs for the hypothetical FLNG vessel is taken from the average cost of Shell's Prelude FLNG; while pipeline, LNG plant, and gas-to-wire costs were obtained from typical industry standards. A typical hyperbolic decline curve model is applied to model depletion flow regime of production life after two scenarios: a 5- and 10-years constant rate plateau time, respectively.
Several factors are included in the sensitivity analysis: LNG price, interest rate, initial production rate, and condensate-to-gas ratio (CGR), distance from shore, electricity price, natural gas price and percentage share of overnight capital cost of building a power plant to convert gas to electricity. The factors are used to gauge their effects on the net present value (NPV) of each scenario and are ranked based on their sensitivity on a tornado chart, with the most sensitive parameter on top, and so on. The analysis suggest that initial production rate has the strongest effect on NPV, followed by discount rate, LNG price, CGR, and the distance from onshore when the reservoir is dry gas. This means the longer the distance from onshore, the more attractive the FLNG alternative becomes. However, when gas price is low, and a subsidy can be obtained, GTW becomes more attractive.
This economic feasibility study will be helpful for future considerations to use FLNG to make offshore gas reservoirs that were previously considered stranded into economically viable resources. The results from this economic model will certainly play a key role in the future of natural gas industry and energy market, especially in West Africa, particularly, in Nigeria.
Overview of Joint Industry Project on Measurement Based Wellhead Fatigue
Authors: Mercan Bulent , Chandra Yenny , Djayaputra Ferdinand , Campbell Mike , Kebadze Buba , Ge Michael , Tognarelli Mike , Lu Wangming , Adams Adrian , Kuzmichev Sergey , Jin Joe , Campbell Brad , Pattillo II P. David , Roveri Francisco , Pestana Rafael , Chen Jinbo , Zhang Heping , Zhang Michael , Fett Darryl , Sanders Richard 
Published: April 2020

AbstractThe objective of the wellhead fatigue joint industry project (JIP) is to provide a measurement-based foundation for drilling riser and wellhead modeling practice in the oil and gas industry and hence to ensure that the fatigue response assessment is performed with adequate but not overly conservative analysis parameters. To this end, the JIP utilizes field measurements from ten (10) drilling campaigns in GoM and North Sea. In order to maintain drilling campaign diversity, the field measurements are selected for a range of environments, water depths (110 to 1,900 m), soil characteristics, riser and wellhead configurations, and vessel types.The study commences with field data QA and filtration. Measurements are classified into wave-dominated events, VIV events and combined wave and VIV events. The finite element models of the as-built riser and wellhead systems are generated using industry standard analysis parameters, and simulations are conducted using measured motions near the top of the riser. The resulting numerical responses for the wellhead are compared with the measured motions to determine the level of conservatism (or otherwise) in the wave fatigue analysis. Additionally, SHEAR7 models driven by measured current profiles are used to compare predicted VIV fatigue response to that based on field measurements.Analysis results indicate that industry standard approach for wave and VIV fatigue assessment is indeed conservative. However, it should be noted that wellhead fatigue predictions through numerical simulations are affected by various analysis parameters, and it is impossible to determine the correct values for each of these parameters by using field measurements alone.In literature, several previous studies compared measured and predicted wellhead response. However, they often focus on a single drilling campaign, which makes it difficult to apply their findings to another drilling campaign. This JIP is the first in the industry to provide a combined assessment of full-scale field data from multiple drilling campaigns. Using consistent analysis techniques for all datasets offers valuable insight into riser and wellhead response characterization and safe drilling operations.
The Emergence of Contact Based Nondestructive Testing NDT at Height Utilizing Aerial Robotic Drone Systems
Authors: Dahlstrom Robert L. 
Published: April 2020

Abstract
Corrosion engineers take Nondestructive Testing (NDT) measurements at height as a method of determining the condition of Oil & Gas and other assets such as flare stacks, boilers, above ground storage and pressure vessels, piping and more. To do this at elevation currently the engineer may need to utilize a lift, scaffolding, ladders, or ropework or even inspection trucks with elevated baskets, sometimes cranes or even specialty access such as rigging catwalks, or other solutions. The engineer will often hold a handheld digital testing device to the asset to take the measurements in these scenarios. While NDT inspection programs can dramatically increase the safety and integrity of infrastructure, industrial and manufacturing assets, access requirements in performing these inspections at elevation introduces risk. NDT inspection sites often require access to elevated areas and require the use of personal fall protection equipment (safety harness and lanyard). Working at height is dangerous, due to the possibility of falls, as well as being time-consuming due to access. In certain instances, it may also require taking an asset, such as a flare stack or chimney stack, offline to allow it to cool so it can be accessed to take NDT readings.
Utilizing an aerial robotics platform that makes contact with a surface in order to gather NDT measurements such as Dry Film Thickness (DFT), Surface Profile (SP), or Ultrasonic Thickness (UT) allows workers to remain safely on the ground. Since there is no need to move a lift, scaffolding or ladders and minimal movements required by the corrosion engineer or the robotic operator, the NDT measurement process can be faster in addition to being safer. Further, since the aerial robotic system (drone) contains onboard computers and sensors it is able to capture a lot of data during the exercise of an NDT inspection regime.
Use of these aerial robotic NDT systems in offshore and marine environments carries unique challenges and operational variables. The Aerial Robotic System described in this paper afford safer, cheaper, and better NDT measurements and allow a more robust viewpoint into assets conditions than the slower and more expensive manual method. While early adopters in the offshore Oil & Gas and maritime industry stand to gain the most from implementing these systems they are also assuming the most risk until the systems become an industrial standard.
Digitalization Deployed: Lessons Learned from Early Adopters
Authors: Nixon John 
Published: April 2020

Abstract
Offshore oil and gas operators may have been slow to realize the potential of the Internet of Things (IoT) and digital transformation, but with the market downturn slowly fading into the rearview mirror, the industry is quickly catching up. Still, there is much that companies can learn from the "early adopters" of digitalization. This paper discusses how digital technologies are being applied in other verticals that are further along the maturity curve (i.e., automotive, manufacturing, marine, aerospace) and how they can be leveraged to optimize the lifecycle performance of offshore oil and gas facilities.
The paper details the benefits of extending digitalization across the energy enterprise to drive down costs and decouple market volatility from profitability. Case studies will be shared from the aforementioned verticals to illustrate how advanced tools, such as digital twins and enterprise product lifecycle management (PLM) solutions have been successfully applied to reduce product cycle times and improve project execution. All of these are highly applicable to upstream oil and gas, and can serve as powerful tools for shortening time to first oil. Overall, the paper aims to provide a broader context for exploration and production (E&P) companies’ digital enterprise strategies.