Remote Sensing in Oil Spill Handling in Offshore North West Java

2021 ◽  
Author(s):  
Audra Ligafinza ◽  
Farasdaq Muchibbus Sajjad ◽  
Mohammad Abdul Jabbar ◽  
Anggia Fatmawati ◽  
Alvin Derry Wirawan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Real Time ◽  
Oil Spill ◽  
Environmental Damage ◽  
Satellite Imaging ◽  
North West ◽  
Novel Technologies ◽  
Oil Boom ◽  
Remediation Strategies ◽  
Restoration Strategies

Abstract During the blowout event, it is critical to track the oil spill to minimize environmental damage and optimize restoration cost. In this paper, we deliver our success story in handling oil spill from recent experiences. We utilize remote sensing technologies to establish our analysis and plan the remediation strategies. We also comprehensively discuss the techniques to analyze big data from the satellites, to utilize the downloaded data for forecasting, and to align the satellite information with restoration strategies. PHE relies on its principle to maintain minimum damage and ensures safety by dividing the steps into several aspects of monitoring, response (offshore and onshore), shoreline management and waste management. PHE utilizes latest development in survey by using satellite imaging, survey boat, chopper and UAV drone. Spill containment is done using several layers of oil boom to recover oil spill, complemented with skimmers and storage tanks. PHE encourages shoreline remediation using nets and manual recovery for capturing oil sludge. Using this combination of technologies, PHE is able to model and anticipate oil spill movement from the source up until the farthest shoreline. This enables real time monitoring and handling, therefore minimum environmental damage is ensured. PHE also employs prudent engineering design based on real time field condition in order to ensure the equipment are highly suited for the condition, as well as ensuring good supply chain of the material availability. This publication addresses the first offshore blowout mitigation and handling in Indonesia that uses novel technologies such as static oil boom, satellite imaging and integrated effort in handling shoreline damage. It is hoped that the experience can be replicated for other offshore operating contractors in Indonesia in designing blowout remediation.

RECENT EXPERIENCE FROM MULTIPLE REMOTE SENSING AND MONITORING TO IMPROVE OIL SPILL RESPONSE OPERATIONS

2008 ◽  
Vol 2008 (1) ◽  
pp. 407-412 ◽  
Author(s):  
Hans V. Jensen ◽  
Jørn H. S. Andersen ◽  
Per S. Daling ◽  
Elisabeth Nøst
Keyword(s):  
Remote Sensing ◽  
Real Time ◽  
Oil Spill ◽  
Chemical Characterization ◽  
Ground Truth ◽  
Lessons Learned ◽  
Recent Experience ◽  
Aerial Surveillance ◽  
Wide Range

ABSTRACT Introducing regular aerial surveillance in 1981 and near-real time radar satellite detection services in 1992, Norway has obtained a substantial experience in multi sensor oil spill remote sensing. Since 2001 NOFO has been a driving force in the development and utilization of ship-based sensors for short to medium range oil spill detection, supplementing airborne and satellite remote sensing. During the NOFO Oil On Water Exercise in 2006 two satellites, four aircraft, one helicopter and two ships carrying wide range of sensors provided a unique opportunity to assess and compare remote sensing field data synchronized with ground-truth sampling from three sampling MOB-boats. The sampling boats were equipped for doing oil slick thickness measurements and physical-chemical characterization of the surface oil properties. A new vessel-based dispersant application system was field tested executing dispersant treatment of two oil slicks while supported by live infrared video transmitted to the vessel from helicopter. The success of this experiment was documented by extensive monitoring and characterization of the surface oil and the dispersed oil plume during and after the dispersant treatment. This guiding technique, in using aerial forward looking IR-video live transmission from helicopter and remote sensing aircraft, has been practiced later during a recent accidental oil spill on the Norwegian continental shelf. To utilize multiple remote sensors operationally from a response vessel, it is necessary to compare signatures from different sensors in near real time. This paper describes core elements of the remote sensing and ground-truth monitoring during oil on water exercises in recent years, lessons learned and how NOFO will continue developing remote sensing operations related to oil spill combating in reduced visibility and light conditions.

Optimized Airborne Oil Spill Remote Sensing: POSEIDON, the Quantitative Approach

2017 ◽  
Vol 2017 (1) ◽  
pp. 1594-1611
Author(s):  
Guilherme Pinho ◽  
Alessandro Vagata ◽  
Theo Hengstermann
Keyword(s):  
Remote Sensing ◽  
Real Time ◽  
Oil Spill ◽  
Oil Spills ◽  
Response Strategy ◽  
Geographical Information ◽  
Web Based ◽  
Incident Command ◽  
Automated Processing ◽  
The Right

ABSTRACT Aerial surveillance is becoming a foundation on the overall oil spill response strategy due to the ability to plan and tactically position response resources in the optimal areas of oil migration. It takes a complete multitasking approach to effectively respond to oil spills. While much of the regulatory focus to date has been on the resources on the sea - vessels, skimmers, dispersants - the reality is that they are only one of the components and not necessarily the most important in combating oil spills. It is imperative to determine the location of oil that is most recoverable, and give quantitative information - thickness, volume, area, classification - whether day or night. Having the right information at the right time optimizes dramatically the use of all the response resources. And assess the effectiveness of the response and make an accurate natural resources damage assessment is critical and requires as well quantitative and timely information. In the past the main effort has been directed towards developing airborne sensors with enhanced spill monitoring capability. Recently, more and more attention has been paid to the automated processing of oil spill data acquired by integrated airborne sensor platforms. Automated processing and real time relay of immediately usable information to the Incident Command Center is critical during all phases of response. This paper focuses on advanced data processing and presents ways of improving the usability of airborne multi-sensor oil spill monitoring systems. In this context, is given an overview of currently existing oil spill remote sensing technology like infrared/ultraviolet line scanners, microwave radiometers, laser fluorosensors and radar system. The paper presents POSEIDON, a system for network-based real-time data acquisition, analysis and fusion of multi-sensor data. Also, a method for the distribution of oil spill data and related data products using web-based geographical information systems is described; automated generation of thematic maps of the oil spill scene along with their real-time web-based distribution is becoming more important in marine incident management.

Real-Time Quantification of Offshore Oil Spills and Environmental Damage During Blow-Out Accident

2021 ◽  
Author(s):  
Steven Chandra ◽  
Farasdaq Sajjad
Keyword(s):  
Real Time ◽  
Oil Spill ◽  
Oil Spills ◽  
Current Speed ◽  
Ocean Current ◽  
Environmental Damage ◽  
Reservoir Characteristics ◽  
Well Completion ◽  
Heavy Hitters ◽  
Offshore Oil

Abstract In the event of offshore oilfield blow-out, real-time quantification of both spilled volume, recovered oil and environmental damage is essential. It is due to costly recovery and restoration process. In order to develop a robust and accurate quantification, we need to consider numerous parameters, which are sometimes tricky to be identified and captured. In this work, we present a new modeling technique under uncertainty, which accommodates numerous parameters and interaction among them. We begin the model by identifying possible parameters that contributes to the process: grouped into (1) subsurface, (2) surface and (3) operations. Subsurface e.g. well and reservoir characteristics. Surface e.g. ocean, wind, soil. (3) Operations e.g. oil spill treatment blow-out rate, oil characteristics, reservoir characteristics, ocean current speed, meteorological aspects, soil properties, and oil-spill treatment (oil booms and skimmers). We assign prior distribution for each parameter based on available data to capture the uncertainties. Before progressing to uncertainty propagation, we construct objective response (amount of recovered oil) through mass conservation equation in data-driven and non-intrusive way, using design of experiment and regression-based method. We propagate uncertainties using Monte Carlo simulation approach, where the result is presented in a distribution form, summarized by P10, P50, and P90 values. This work shows how to robustly calculate the amount of recovered oil under uncertainty in the event of offshore blow out. There are several notable challenges within the approach: 1) determining the uncertainty range in blow-out rate in case of rupture occurs in the well, 2) obtaining data for wind and ocean current speed since there is an interplay between local and global climate, and 3) accuracy of capturing the shoreline geometry. Despite the challenges, the results are in-line with the physics and several recorded blow-out cases. Define what is blow out rate (important as has highest sensitivity). Through sensitivity analysis with Sobol decomposition (define this …), we can define the heavy hitters. These heavy hitters give us knowledge on which parameters should be aware of. In real-time quantification, this analysis can provide an insight on what treatment method should be performed to efficiently recover the spill. We also highlight about the sufficiency of the model to obtain several parameters’ range, for example blow-out rate. The model should at least capture the physics in high details and incorporate multiple scenarios. In the case of blow-out rate, we extensively model the well completion and consider leaking due to unprecedented fractures or crater formation around the wellbore. We introduce a new framework of modeling to perform real-time quantification of offshore oil spills. This framework allows inferring the causality of the process and illustrating the risk level.

An assessment of toxic metals content in the marine sediments of the Shuaiba Industrial Area, Kuwait, after the oil spill during the Gulf War

1996 ◽  
Vol 34 (7-8) ◽  
pp. 203-210 ◽  
Author(s):  
S. Al-Muzaini ◽  
P. G. Jacob
Keyword(s):  
Oil Spill ◽  
Marine Sediment ◽  
Oil Spills ◽  
Industrial Area ◽  
Gulf War ◽  
Oil Wells ◽  
Environmental Damage ◽  
Base Line ◽  
Sampling Locations ◽  
Very High

A field study was carried out involving seven fixed sampling stations. The sampling locations were selected to cover the distribution of pollutants in the Shuaiba Industrial Area (SIA), which was contaminated with oil released from oil wells and broken pipelines and with a vast amount of burnt and unburnt crude oil from the burning and gushing oil wells. The samples were collected biweekly between July 1993 and July 1994. The concentrations of V, Ni, Cr, Cd and Pb were determined and compared with the previously collected baseline data to assess the degree of environmental damage caused due to the oil spills during the Gulf war. The average concentrations (mg/kg) of various elements in the marine sediment were 17.3 for V, 30.8 for Ni, 55.5 for Cr, 0.02 for Cd and 1.95 for Pb. Our results show that even after the heavy spillage of oil, associated metal concentrations were not very high compared with previously reported base line values.

scholarly journals Real-Time Semantic Segmentation of Remote Sensing Images Based on Bilateral Attention Refined Network

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 28349-28360
Author(s):  
Jiali Cai ◽  
Chunjuan Liu ◽  
Haowen Yan ◽  
Xiaosuo Wu ◽  
Wanzhen Lu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Real Time ◽  
Semantic Segmentation ◽  
Remote Sensing Images

scholarly journals Modeling and Simulation of Mission Planning Problem for Remote Sensing Satellite Imaging

2018 ◽  
Vol 179 ◽  
pp. 03024 ◽  
Author(s):  
Yao Pan ◽  
Zhong Ming Chi ◽  
Qi Long Rao ◽  
Kai Peng Sun ◽  
Yi Nan Liu
Keyword(s):  
Remote Sensing ◽  
Time Window ◽  
Constraint Satisfaction Problem ◽  
Optimal Path ◽  
Time Constraint ◽  
Mission Planning ◽  
Planning Problem ◽  
Satellite Imaging ◽  
Problem Model ◽  
Remote Sensing Satellite

Mission planning problem for remote sensing satellite imaging is studied. Firstly, the time constraint satisfaction problem model is presented after analyzing the characteristic of time constraint. Then, An optimal path searching algorithm based on the discrete time window is proposed according to the non-uniqueness for satellite to mission in the visible time window. Simulation results verify the efficiency of the model and algorithm.

scholarly journals Electric Cell-Substrate Impedance Sensing To Monitor Viral Growth and Study Cellular Responses to Infection with Alphaherpesviruses in Real Time

mSphere ◽  
2017 ◽  
Vol 2 (2) ◽  
Author(s):  
Matthew R. Pennington ◽  
Gerlinde R. Van de Walle
Keyword(s):  
Real Time ◽  
Cellular Response ◽  
Cellular Responses ◽  
Cellular Damage ◽  
Impedance Sensing ◽  
Novel Technologies ◽  
Antiviral Therapies ◽  
Mucosal Surfaces ◽  
Cell Substrate ◽  
Hsv 1

ABSTRACT Alphaherpesviruses, including those that commonly infect humans, such as HSV-1 and HSV-2, typically infect and cause cellular damage to epithelial cells at mucosal surfaces, leading to disease. The development of novel technologies to study the cellular responses to infection may allow a more complete understanding of virus replication and the creation of novel antiviral therapies. This study demonstrates the use of ECIS to study various aspects of herpesvirus biology, with a specific focus on changes in cellular morphology as a result of infection. We conclude that ECIS represents a valuable new tool with which to study alphaherpesvirus infections in real time and in an objective and reproducible manner. Electric cell-substrate impedance sensing (ECIS) measures changes in an electrical circuit formed in a culture dish. As cells grow over a gold electrode, they block the flow of electricity and this is read as an increase in electrical impedance in the circuit. ECIS has previously been used in a variety of applications to study cell growth, migration, and behavior in response to stimuli in real time and without the need for cellular labels. Here, we demonstrate that ECIS is also a valuable tool with which to study infection by alphaherpesviruses. To this end, we used ECIS to study the kinetics of cells infected with felid herpesvirus type 1 (FHV-1), a close relative of the human alphaherpesviruses herpes simplex virus 1 (HSV-1) and HSV-2, and compared the results to those obtained with conventional infectivity assays. First, we demonstrated that ECIS can easily distinguish between wells of cells infected with different amounts of FHV-1 and provides information about the cellular response to infection. Second, we found ECIS useful in identifying differences between the replication kinetics of recombinant DsRed Express2-labeled FHV-1, created via CRISPR/Cas9 genome engineering, and wild-type FHV-1. Finally, we demonstrated that ECIS can accurately determine the half-maximal effective concentration of antivirals. Collectively, our data show that ECIS, in conjunction with current methodologies, is a powerful tool that can be used to monitor viral growth and study the cellular response to alphaherpesvirus infection. IMPORTANCE Alphaherpesviruses, including those that commonly infect humans, such as HSV-1 and HSV-2, typically infect and cause cellular damage to epithelial cells at mucosal surfaces, leading to disease. The development of novel technologies to study the cellular responses to infection may allow a more complete understanding of virus replication and the creation of novel antiviral therapies. This study demonstrates the use of ECIS to study various aspects of herpesvirus biology, with a specific focus on changes in cellular morphology as a result of infection. We conclude that ECIS represents a valuable new tool with which to study alphaherpesvirus infections in real time and in an objective and reproducible manner.

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