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Remote Sensing and Detection of Oil Spill Dispersions

Dissertation
Author: Akinwande A. Elewa
Abstract:
The research problem was to understand how to develop a secure and reliable wireless sensor network for remote oil spill detection and monitoring, resulting from leaks from unmanned production platforms. The purpose of this quantitative single case study was to test information assurance of remote sensing data and information for offshore oil spills. The double-loop learning model proposed by Argyris and Schön provided the conceptual framework to determine if a paired parallel sensor configuration could provide a means for immediate and reliable oil spill detection. Data were collected from the environmental sensor installation of one corporate sensor network. Cycling across the ABA baseline/test condition served as the independent variable; whereas oil spill sensor data indicating the confirmation of oil spill, proof of information integrity, and other parameter readings served as dependent variables. Streaming sensor data was aggregated before and after the ABA phase shifts and analyzed using a standardized statistical quality control protocol. Statistical analysis included C statistics for serial dependency, F test and z -test for sample means, and Cohen's d test for intervention effect. Statistically significant differences in oil spill signal data were observed and coinciding with the ABA phase shifts. These results supported the conclusion that the accuracy and assurance of sensor data and information can be demonstrated in actual field environments. Based on the findings, an interactive remote sensing network for organization learning in information assurance setting was modeled for proactive use to data driven corporate security practices. Implications for positive social change included the timely warning from remote oil spill sensing that can result in improved safety and protection for the environment, employees, the public, and equipment.

Table of Contents List of Tables ..................................................................................................................... iv List of Figures ......................................................................................................................v Chapter 1: Introduction to the Study ....................................................................................1 Study Background .......................................................................................................3 Problem Statement.......................................................................................................7 Purpose of the Study ....................................................................................................8 Research Questions and Hypotheses ..........................................................................8 Nature of the Study ......................................................................................................9 Theoretical Base .........................................................................................................12 Definition of Terms ....................................................................................................13 Assumptions................................................................................................................15 Scope and Limitations ...............................................................................................15 Delimitations ...............................................................................................................16 Significance of the Study ...........................................................................................16 Significance to Management ........................................................................ 16 Significance to the Industry ......................................................................... 16 Positive Social Change Aspects .................................................................... 17 Summary and Transition Statement ........................................................................17 Chapter 2: Literature Review .............................................................................................19 Organization of Literature Review ..........................................................................20 Organizational Critical Infrastructure Protection; Research Design Focus ........21 Sensor Information Transmission ............................................................................23 Wireless Sensor Networks Design Issues .................................................... 23 Sensor Network Architecture ...................................................................... 26 Sensor Network Standards........................................................................... 28 Sensor Network Protocols and Communication Architectures ................ 29 Sensor Network Routing .............................................................................. 35 Location Awareness in Wireless Sensor Networks .................................... 38 Data Aggregation .......................................................................................... 38 Wireless Sensor Networks Information Security and Assurance Issues. .............39 Access Control Issues .................................................................................... 41 Current Researches in Remote Oil Spill Sensing ....................................................45 Organizational Learning Context: Organizational Information System Focus................................................................................................................47 Summary, Discussions, and Transition Statement .................................................49 Chapter 3: Research Method ..............................................................................................51

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Research and Design ..................................................................................................51 Advantages and Disadvantages of Quantitative Research Designs .......................52 Advantages..................................................................................................... 52 Disadvantages ................................................................................................ 52 Restatement of Problem Statement, Research Question, and Purpose of Study................................................................................................................53 Hypothesis ...................................................................................................................53 Research Design .........................................................................................................54 Design Rationale............................................................................................ 54 The Unit of Analysis, Population, and Sampling Plan ...........................................55 Population and Sampling Plan .................................................................... 57 Validity and Reliability..............................................................................................59 Validity ........................................................................................................... 59 Reliability ....................................................................................................... 61 The Variables .............................................................................................................62 Data Collection and Analysis ....................................................................................64 Data Collection Procedures .......................................................................... 64 Data Analysis Procedures............................................................................. 65 Summary, Discussions, and Transition Statement .................................................66 Chapter 4: Results ..............................................................................................................67 Research Question and Hypothesis Testing ............................................................71 Research Question 1 ..................................................................................... 71 Research Question 2 ..................................................................................... 72 Testing Study Hypothesis 1 .......................................................................... 73 Testing Study Hypothesis 2 .......................................................................... 75 Synopsis of Test Results................................................................................ 78 Summary, Discussions, and Transition Statement .................................................79 Chapter 5: Summary, Conclusion, and Recommendations ...............................................80 Interpretation of Findings ............................................................................ 82 Recommendations for Action....................................................................... 84 Study Social Change Implications ............................................................... 85 Recommendations for Future Research ..................................................... 87 Conclusion ..................................................................................................................87 Concluding Statement .................................................................................. 89 References ..........................................................................................................................91 Appendix A: Descriptive Statistical Summary ................................................................101 Appendix B: Statistical Summaries .................................................................................102 Appendix C: Statistical Control Charts............................................................................106

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Appendix D: Normal Distribution Q-Q Plot ....................................................................108 Appendix E: Z-tests for Phase Transitional Comparisons ...............................................110 Appendix F: Nonparametric Mann-Whitney U Test .......................................................111 Appendix G: Cohen’s d for Effect Verification ...............................................................112 Appendix H: Permissions ................................................................................................113 Permission Request Letter to Yole Dévelopment ..................................... 113 Permission Request Letter to NOAA ........................................................ 114 Curriculum Vitae .............................................................................................................115

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List of Tables Table 1 Sample size determination ................................................................................... 60

v List of Figures Figure 1. Causes leading to oil spill events ....................................................................... 1 Figure 2. Typical organizational oil spill response model ................................................ 4 Figure 3. Dynamics of oil spill impact on oil and gas offshore producing organizations . 5 Figure 4. Evolution in Microelectromechanical market .................................................. 25 Figure 5. Wireless sensor architecture ............................................................................. 27 Figure 6. Typical remote environmental sensing architecture ........................................ 30 Figure 7. Typical corporate protocol stack ...................................................................... 34 Figure 8. Multihop routing of sensed event data ............................................................. 36 Figure 9. Multihop routing coverage of sensed event data ............................................. 37 Figure 10. Sample size determination for population mean ............................................ 60 Figure 11. ABA single-subject reversal research design rendering ................................ 63 Figure 12. ABAB single-subject multiple baseline research design rendering ............... 63 Figure 13. Result visualization for “A – B - A” variables............................................... 67 Figure 14. Normal distribution rendering of the baseline, from raw data ....................... 69 Figure 15. Normal distribution rendering of the intervention, from raw data ................. 69 Figure 16. Normal distribution rendering of the reversal, from raw data ....................... 70 Figure 17. Response-driven model of information assurance for an oil-spill event ....... 87

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Chapter 1: Introduction to the Study With the increase in environmental occurrences around the world today, it is evident that technological advancement in production environments has not made the planet a better place to live. Numerous international occurrences have shown this is not the case. Production workflow systems have improved lives and have advanced left- behind civilizations. These systems, untamed, have also caused incalculable havoc to the environment at large. Oil Spill Events Deliberate Acts Negligence Production Effluents Equipment Malfunctions Environmental Factors Accidents Resurfaced Oil From Poor Cleanups

Figure 1. Causes leading to oil spill events As shown in Figure 1, developed by the researcher, these pollution causes are numerous and in various forms. Causes can range from human activities, such as equipment use, poor cleanup, and unregulated garbage disposal, to causes such as accidents and equipment malfunction resulting in spill dispersions from offshore production systems. According to the United States Coast Guard (2006), more than 7 million gallons of oil were spilled in 2005 during Hurricane Katrina from various sources, industrial plants included.

2 The world has seen numerous cases of oil spills from various organizations and in various locations. Examples involve the 71,000 barrels spilled in the Calcasieu River, Louisiana, on June 19, 2006. On August 11, 2006, 530,000 gallons of oil spilled in Guimaras, an island in the Philippines, due to an incident of a tanker sinking, with extensive fishing grounds destroyed. Another environmental disaster occurred with 12 miles of beach affected from 2.8 million gallons of oil spilled from a collision of two ships in South Korea on December 7, 2007 (Infoplease, 2009). As this paper is written, an estimated 750,000 gallons of oil/day is spewing into the Gulf of Mexico in an offshore platform mishap — an incident the world has never experienced. Inadequacies in operations and the lack of regulatory enforcements and supervision of inattentive organizations have helped encourage carelessness and the way the planet is being polluted daily. The National Oceanic and Atmospheric Administration (NOAA) reported that the environmental impact of the Exxon Valdez spill of 1989 still persists. These delays in the decomposition are happening in areas where weathering process are weaker (NOAA, Assessing Environmental Harm, 2010). The negative effects of oil spills to the environment are immense. In July 25, 2008, an oil spill from a barge in a collision released an estimated 419,000 barrels of heavy oil in the Mississippi River. This spill adversely affected the local wildlife and the river traffic. Adding to these negative effects is the destruction of river coastal areas, which destroyed the livelihood of thousands of anglers and recreational boat operators. The ability to detect and respond quickly is important, to limit environmental impact from oil spills occurring from all sources.

3 Quick detection and removal of oil spill from offshore production systems, especially from offshore platforms is of utmost importance. The protection of corporate networks from penetration and attacks is required during the transmission of the detected data to first responders and stakeholders, confidentially, without compromising the information content and authenticity. Thus a secure network is essential for safeguarding and protection of proprietary information. Study Background It is a widely known fact that offshore oil- and gas-producing organizations are experiencing production losses from unplanned shutdowns from offshore production platforms. These shutdowns happen because the unmanned platforms are susceptible to hydraulic leaks and other used oil leaks. While alarms from oil reservoirs indicate the dropping oil tank levels, the actual damage is done by the time the responders arrive. It is not uncommon for an organization to lease helicopters for site surveys during these cases to look for sheens on the ocean surfaces. These costly expenses from shutdowns and surveys have reduced the bottom line of these oil- and gas-producing organizations. As shown in Figure 2, developed by the researcher, process alarms are unreliable, even though the responsible operator depends on these for spill events. The issue is further compounded with the use of costly spill search flights. Due to lack of information assurance there is no way of knowing what the reaction and response to any of such unreliable flights will be, as it depends on whatever was found. During the waiting period for all of these search flights to provide certain feedback, the actual cleaning is delayed, thus more oil spill will ensue. Also, these flights are visual only; the machines

4 do not carry any special spill-sensing or detection systems to enhance uncomplicated discoveries. Oil Spill Notification via Alarms Operations Notification Operations Mobilization Request Oil Spill Location Flight Confirmation Corporate Stakeholders Logistics Aid Response Tools & Materials Regulatory Stakeholders Reporting Health Safety & Environment Reporting/ Database Update Confirmation of Complete and Total Cleaning Cleaning Process

Figure 2. Typical organizational oil spill response model In production systems, everything is related and must work together as planned to provide the designed results. When a part of the process is shut down, either planned or unplanned, everything is affected. An oil spill event will cause the production line and all systems to be shut down for investigation for possible leak causes. The severity of the incident will be a factor in the rate of recovery from the shutdown. The financial goals and planning are also affected as a result of the shutdown, no matter how short the duration is.

5

Figure 3. Dynamics of oil spill impact on oil and gas offshore producing organizations In Figure 3, developed by the researcher, it is clearly shown how and why every effort not to have a spill counts and more so, if it has happened what the influence of the response rates on production and the environment will be. The faster the rate of response, the quicker the cleanup will be. This quick cleanup will subsequently help the environment, and then production can be resumed quickly. Ambient factors, namely, temperature, humidity, rainfall, snowfall, tides, and currents, will affect the dispersion rates, cleanup efforts, and the physical properties of the spilled oil in several ways. The probable properties are density, viscosity, emulsification ability, solubility, and evaporation rate.

6 A dependable oil spill detection system must be commonplace for offshore operators in avoiding false detection alarms. A repeat of these kinds of occurrences in a year can be challenging, even to the skillful manager. Regulatory requirements also mandate that these types of offshore effluents be reported from production platforms as soon as they happen. The absence reporting these effluents can result in heavy fines. Organizations have incurred significant fines and these costs can be substantial. To be a model organization, image and reputation are as critical. Reporting these spills can be detrimental due to the damage it can do to the company’s reputation. Reputation damage will be worse when a competitor, a network violator, a careless worker, an intruder, a disgruntled employee or a hacker looking for fame cause harm out of spite. Organizations must protect their networks, reputation, image, revenue, and organization at all costs as a strategic plan to be competitive. Timely reporting of technologically authenticated recordable spills from the main sources will advance any organization’s credibility. This research is about remote sensing and detection of oil spills via wireless sensor networks in a content analysis setting, the assurance and integrity of detected signals, and the processing of the transmitted data. Other aspects of this study will include the security of the spill detection network, which will deliver information only to the stakeholder in a role-based access control (RBAC) setting. Statistics will be used in this quantitative single subject content analysis study design. This study will fill the production operations oil spill surveillance and remote sensing information assurance knowledge base.

7 Problem Statement The problem to be researched in this dissertation was the lack of understanding of how to develop a secure and reliable wireless sensor network for remote oil spills detection and monitoring resulting from leaks from unmanned production platforms. Equipment, even when adequately maintained has resulted in numerous unplanned downtime, for organizations in the preceding years. Often, the use of costly unplanned flights to monitor ocean surface for sheen from oil spills from hydraulic system leaks and production effluents have become routine. A readily available and dependable sensor network for surveillance and monitoring of ocean surfaces that will confidentially transmit authenticated information with integrity will allow for improvements. Organizations will be able to respond to change, maintain their reputation, report every spill incident adequately and timely without fear, thus drastically decreasing downtime, anxiety, and losses. Operationally defined from a convenience sampling with permission of the production platform archival records, the population size is determined as N =1, with observations. Variable 1 is the observation data points at the baseline, identified as the period of little or no detection activity, as recorded. Variable 2 is the observation at the control / “treatment” data points period when when the intervention is applied, there are dtection activities being recorded. Variable 3 is the data points period of reversal back to baseline, when the intervention is removed, with little or no detection activities. The data to be collected were generated without any outside or special influnces in a continued measurement stream. A stabilization period exists between different

8 phase variables for the identification of the variations between baseline and treatment periods. Statistical analyses to be considered include statistical process control of each variable to ensure stability; tests of statistical significance, z–test for two population means in a paired difference, and the determination between means of the three population variables. Purpose of the Study The purpose of this quantitative single-subject content analysis study was to test information assurance for remote sensing of offshore oil spills and organizational learning theories in relation to oil spills as the independent variables, to oil spill detection, and confirmation as controlling dependent variables for organizations. The independent variables were the environmental untagged parameters, such as date, time, and sensor data, which will be generally defined as process hidden information. The dependent variables were spill cofirmation, proof of information integrity, and other parameter readings, which will be statistically analyzed in the study. Research Questions and Hypotheses For a situation in which existing spill management and response systems are unreliable, questions to ask include: How do the baseline, treatment/intervention, and reversal sensor signals compare in value for all periods? How are the treatment/intervention sensor signal values, a confirmation of an oil spill?

9 These questions are very relevant in all aspects of the integrity of the generated data, information assurance of the system, data processing, and storage. Without successfully finding answers to these questions, a would-be intruder from a standby boat or from elsewhere can hijack these data and information for malicious purposes. Corporate actions are required if the organization’s reputation is to be protected and anxiety curbed. To address the research questions, two hypotheses are proposed: H 01: Both baseline sensor signals and spill confirmation signals/intervention come from the same population sample, thus µ 1 = µ 2 = µ 3 = 0, (or µ 1y = 0). H a1: Both baseline sensor signals and spill confirmation signals/ intervention are not from the same population sample, thus µ 1 ≠ µ 2 ≠ µ 3 ≠ 0 (or µ y ≠ 0, a two-tailed test). H 02: Both baseline sensor signals are equal in value with the spill confirmation signals/treatment value, thus µ 1 = µ 2 = µ 3 = 0 (or µ 2y = 0). H a2: Both baseline sensor signals are not equal in value with the spill confirmation, thus µ 1 < µ 2 > µ 3 > 0. (or µ y ≠ 0, a two-tailed test). This is a test of whether the design gives a higher sensor signal value of the treatment. Nature of the Study An individual operation and production platform, conveniently selected among others served as the unit of analysis. In order to increase the generalizability of findings, a replicated single-subject approach was favored with random sample size determination. This design included an analysis of collected data, based on the research questions

10 guiding the study. A quantitative study approach in a single-subject content analysis study was proposed for this investigation, given the nature of the research questions. This study belongs to the classification of quantitative research designs, which consist of (a) randomized or experimental, (b) quasi-experimental, (c) meta-analysis, (d) correlation studies, (e) existing data, (f) survey design, and (g) causal comparative. From these designs, the most compatible method selected among others that were considered, but not selected for this study, is the quasi-experimental study from existing data sources. Given the nature of the study, a quasi-experimental method with single subject design, individual differences in sleep-wake-sleep periods of sensor activities can be easily demonstrated. Although the listed research methods are popular and widely used, they are not compatible and offer no resolution in answering the research question. In traditional in-subject designs repeated measures or individual treatment are required for a study. The study of an individual can be carried out over a lengthy period of time, which can lead to a very high cost. Group data may not represent individual behavior, a removal from the research question, and erroneous results can ensue. Single subject or small N designs addresses changes in one subject over time and motivated conditions. As declared by Jones (2006) other methods from single subject design cannot provide the require information, it enhances practice quality. Other justifications for this selection included the ease with which it can be conducted. The treatment effectiveness can be easily demonstrated. This research method allows for the investigation and experimental evaluation of treatment/control of one individual behavior, in this case the

11 sensor under study. Ethical issues can be avoided by withholding treatment from control group Quantitative variables were evaluated numerically and analyzed statistically. First, the statistical quality control of the baseline, intervention, and reversal were conducted to ensure period consistency. This control was followed by analysis of variance (ANOVA) of the periods. A statistical significance z-test was conducted to a change from the baseline to intervention to the reversal phases. An analysis of the variability and commonality of the study outcomes across tested cases provided a basis for drawing conclusions. Data collection for this study was from an existing sensor installation for environment monitoring in an operational setting. Infused data are recorded by installed sensors transmitted wirelessly to a network gateway, where data are routed via a transfer protocol for data verification, assignment, and interpretive database. Clients, based on their role in the organization, will be able to securely access the information in real time, via wireless access or other access, using user-friendly graphical user interfaces. Sample data to be collected included and was not limited to date, time, sensor response levels, and geographical location. Other physical data that may be required came from relevant process trends. The sample size determination is described in detail in the “Unit of Analysis, Population, and Sampling Plan” section of this study. Frequency of successes and failure and anomaly detection were reported. These rates will enable organizations to compare real savings data from incident prevention resulting from the newly improved changes to previous downtime.

12 The accuracy and reliability of collected data was confirmed in hypothesis 1 by the use of single subject reversal baseline data analysis. This confirmation allowed for causal inference and evaluation of the situation in a content analysis design. The influence of the “interventions” will be evaluated as it brings about the changes in the dependent variable. To assure confidence in the collected data, using SPSS software, Nonstationary Time Series correlation analysis of collected data was used to confirm hypothesis 2. The accuracy, authentication, of the data was confirmed through the use of statistical analysis. Theoretical Base The terrorist attacks on September 11, 2001, called to attention the critical need in responding to terrorism of all forms and magnitudes. Although concerns over information assurance and corporate security preparedness against terrorism have escalated in recent years, little empirical research has been conducted in information assurance for offshore oil production. There is neither a universal definition of this awareness nor have factors of watchfulness been clearly outlined by management experts in corporate disasters. The theories that guided the research questions are the organization learning, in particular the Argyris and Schön (1978) double-loop learning model, information security, and processing theories. As a change model, double-loop learning provided the needed ingredient for organizations to become a learning organization while information processing theory reinforced the data and information being handled.

13 The research design, which is a single subject design, was guided by problem mapping from organizational systems. This design is followed by a new model proposal, a testable prediction from collected data, with information assurance as the focus of the main principle. It is hoped that the conditions specified by the new model will be adopted and incorporated into the organization’s workflow system for offshore production. Two main categories are prominent in single subject content analysis designs, which are the baseline categories and the intervention or treatment categories. According to Creswell (2009) observations in these categories are made over time. Comparing the two categories as a control by itself helps to revisit organizational theory-in-action and experiences to predict the future. In oil spill incidences, a change rarely occurs to any monitoring system until interventions occur or are enabled. Therefore there is a strong relationship between independent variables as governing principles and the dependent variables as consequences. The Argyris and Schön (1978) organizational change model was perfect for this study. Double-loop learning enables organizations to incorporate the new ideas of information assurance and lessons learned from consequences of remote spill detection responses to revaluate the governing variables. This approach would help organizations become a better learning organization with renewed focus on information assurance. Definition of Terms ABA design. A single baseline design depicts an initial baseline stage “A,” then a treatment “B,” and a return to the baseline “A,” a reversal or withdrawal design.

14 Behavior changes are observed on the introduction of the treatment and reverses when the treatment is removed (Creswell, 2009). Access control. Mechanism for controlling user-accessible resources and user- performable tasks (Tulloch, 2003). Authentication. Defining the parameters about who can access a network (Tulloch, 2003). Availability. Timely and reliable access to data and information services for authorized users (Calder & Watkins, 2007). Confidentiality. Denoting safety from interception, viewing, and copying (Tulloch, 2003). Dispersion. Natural wave action caused distribution of spilled oil into the top layer of a water column (NOAA, 2006). Incident response. Taken action in response to an incident, either affecting security or a process (Tulloch, 2003). Identity theft. Impersonation by stealing the identity that belongs to someone else (Tulloch, 2003). Impact analysis. Analysis and financial evaluation of the likely outcome of the successful exploitation of vulnerability, by a threat, considering the asset’s availability, confidentiality, or integrity (Calder & Watkins, 2007). Information assurance. Methodologies ensuring information security (Tulloch, 2003).

15 Integrity. Accuracy and completeness of received data or information (Tulloch, 2003). Intrusion Detection System. Application or device use for the identification of questionable network activities (Tulloch, 2003). Nonrepudiation. Ability to proof who performed an action, as sending a message and preventing the authorship denial, of a sent message, at a later date (Tulloch, 2003). Assumptions This study was to fill the needed void regarding corporate information awareness as regards offshore oil spill incidents with the organizational information systems infrastructure in mind. It was assumed that other forms of offshore oil spill data and information assurance may have existed or come into play in one form or another while this study was being conducted; however, it was not discovered in literature search. This research study assumed that the collected data were true representative of sensor- generated data and therefore valid. Scope and Limitations The approach taken in this study was limited to information assurance of generated data from production platforms. The study was also limited to wireless sensors as a means of data collection via remote sensing network application and did not include other forms of data collection. Another limitation in this study was that, the research design selected would at the same time provide the sample treatment and control required for a single subject content analysis. Due to the nature of this study the inadequacy and unavailability of simulation facilities, the data collected were limited to archival or

16 existing data. The interpretive schemes included line graphs for baseline and treatment observations. This would have the treatment observations on the abscissa and units of time at the ordinate. Delimitations This study attempted to identify the problems as they stand today and potentials of fraudulent activities within the company’s information network system, using currently available data and information. An individual offshore production operation platform, among others, in the population served as the unit of analysis for this study. This study did not investigate shutdown resulting from oil spills effect on detailed production numbers and revenue of organizations. This study was generalized to offshore oil and gas producing organizations. Significance of the Study Significance to Management This study reduced the oil and gas production operations surveillance and management knowledged base gap. Upbeat morale and anxiety reduction for personnel, increased production, ontime emergency response, and equipment reliability were some of the benefits that were realized from this study. Cost and expenses reduction from false alarms will be eliminated. Significance to the Industry Oil and gas organizations should benefit immensely from this study and the findings will enable them to emerge as learning organizations, with a new approach for

17 data processing, information assurance, and security. This study should be invaluable and significant to the management of any organizations’ daily operation. Industrial image enhancement with new technology is anticipated with this study. Positive Social Change Aspects Environmental, public, and employee safety and protection are anticipated. The general public will stand to gain from the added safety features via the real-time monitoring that the study should bring to the offshore production operations. Loss of revenue that seldom results from continental oil spill incidents will also be addressed in time. This study also provided reduced risks in preventing another Gulf oil spill that is still ongoing as this paper is written. The Gulf oil spill incident that has negatively affected lives and businesses in the area. Summary and Transition Statement The main theme of this chapter was to build the case for organizations to report all cases of spills willingly and without duress, if they have at their disposal an effective and dependable spill monitoring system. Chapter 1 introduced the proposed study with a description of the current international concerns about offshore oil spills. The chapter included the problem statement, purpose of the study, nature of the study, conceptual framework, operational definitions, assumptions, scope limitations and delimitations; significance of the study, and brief descriptions of the succeeding chapters, followed by a summary and discussions. Chapter 2 is the literature review, wherein an in-depth analysis of the supporting literatures will be deliberated. Chapter 3 covers the research methodology, data

Full document contains 128 pages
Abstract: The research problem was to understand how to develop a secure and reliable wireless sensor network for remote oil spill detection and monitoring, resulting from leaks from unmanned production platforms. The purpose of this quantitative single case study was to test information assurance of remote sensing data and information for offshore oil spills. The double-loop learning model proposed by Argyris and Schön provided the conceptual framework to determine if a paired parallel sensor configuration could provide a means for immediate and reliable oil spill detection. Data were collected from the environmental sensor installation of one corporate sensor network. Cycling across the ABA baseline/test condition served as the independent variable; whereas oil spill sensor data indicating the confirmation of oil spill, proof of information integrity, and other parameter readings served as dependent variables. Streaming sensor data was aggregated before and after the ABA phase shifts and analyzed using a standardized statistical quality control protocol. Statistical analysis included C statistics for serial dependency, F test and z -test for sample means, and Cohen's d test for intervention effect. Statistically significant differences in oil spill signal data were observed and coinciding with the ABA phase shifts. These results supported the conclusion that the accuracy and assurance of sensor data and information can be demonstrated in actual field environments. Based on the findings, an interactive remote sensing network for organization learning in information assurance setting was modeled for proactive use to data driven corporate security practices. Implications for positive social change included the timely warning from remote oil spill sensing that can result in improved safety and protection for the environment, employees, the public, and equipment.