Detecting unexploded ordnance (UXO) at sea is a demanding task. UXO survey data is acquired using a set of different sensors in different configurations and can cover large areas. To ensure that the resulting highly complex data set is fit for purpose, a well-defined workflow is crucial. Researchers in the BASTA project are therefore developing quantitative data quality factors to indicate how survey data should be acquired for the detection of a specified reference object.

Ammunition or unexploded ordnance (UXO) at sea poses a threat during offshore work such as the construction of pipelines or platforms, as well as to the marine environment. If UXO detection and remediation activities are performed incorrectly, mismanaged, or even omitted, UXOs can threaten the lives of construction workers, the construction schedule, marine life and the public image of the parties involved. . In response to these challenges, Frey (2020) developed the Quality Guideline for the Disposal of Explosives and Ammunition at Sea (EOD). The directive addresses the four phases of DOE: (I) a preliminary investigation of historical data records, (II) a technical field investigation, (III) an investigation of suspect UXO sites, and (IV) elimination and elimination of UXO. Other guidelines on UXO marine surveys or hydroacoustic mapping that are relevant to ammunition surveys have been published by OWA (2020), IHO (2020), NOAA (2019) and IOGP (2009). All of these documents largely consist of a qualitative description of the workflows of marine geophysical surveys and, to some extent, of UXO campaigns. GEOMAR and EGEOS are currently working on a method to quantitatively describe a survey by defining data quality factors. Using such quality factors in the workflow can improve data processing, as more time can be spent analyzing and interpreting the data. As multi-sensor datasets become larger and more complex, a well-defined workflow and consistent threshold criteria for data quality will increase project transparency and confidence in the results. In addition, clear definitions will improve communication between all partners involved in UXO projects, from the project manager to surveyors and data analysts.

Methodology

BASTA researchers apply the following steps to define data quality factors:

1. A literature review of all existing guidelines. Based on this information, a first table of data quality factors for the reference object and for the various relevant sensors (multibeam echosounder, side scan sonar, sub-bottom profiler, magnetism) could be developed.
2. This first table of data quality factors was transformed into a questionnaire and sent to 125 experts in the field of marine UXO surveys. An updated table was then created based on the responses.
3. Digital workshops for stakeholders were held to discuss data quality factors and cut-off values ​​that define whether the data is fit for the purpose of detecting a specified reference object. Two workshops for each of the magnetic and hydroacoustic sensors were organized and 29 experts participated in the discussions. The workshops resulted in final agreement on 57% of the data quality factors discussed, while the rest is still under discussion. Again, the table of data quality factors has been updated.
4. In a last event, which will take place during Kiel Ammunition Clearance Week 2021, other quality factors, not yet agreed, will be discussed in more detail.

Data quality factors – Preliminary results

General definition

We distinguish between the data quality factors of the reference object and the data quality factors of the sensors. In the process described above, these were identified by answering the following questions:

• Reference object: What data quality factors of the reference object should be provided after preliminary investigation and before sensor selection?
• Sensors: What factors of sensor data quality are important in determining whether the survey data is suitable for detecting a specified reference object?

Once these questions are answered, a standardized UXO survey workflow based on transparent data quality factors could be developed. A preliminary version of the workflow for multibeam surveys is shown in Figure 1.

The organization chart shows that the historical study and the documentation of the site conditions are the main contributions to the definition of a reference object. It is the smallest object that should be detectable in survey data and is typically defined as a result of a threat or risk assessment. All the quality factors of the reference object are therefore a result of the preliminary investigation (phase I). Note that not all the quality factors of the reference object are relevant for multibeam systems, because the reference object must be defined (and therefore its quality factors determined) before the start of the survey planning. .

The reference object and its properties are the input data of the technical study (Phase II), in which the measurement methods are defined and then reviewed and revisited by the client and the contractor during the call for tenders. and the definition of the method statement for the study. In addition, a number of survey parameters define how the survey process itself is performed. The method statement must therefore balance the data quality requirements with the survey feasibility requirements. Knowledge of all data quality factors is relevant for subsequent data processing and interpretation processes.

Similar workflows have been prepared for all sensors commonly used in UXO detection surveys and are available on the BASTA project site. These include the multibeam echosounder, side scan sonar, underwater profiler and magnetometer (Frey 2020). More recent techniques such as electromagnetism, synthetic aperture sonar and possibly chemical sensors will be defined in the future.

For the quality factors of the sensor data, threshold values ​​must be defined for the sensor. These act as an objective and theoretical requirement for the detection of the specified reference object. Since the data quality factors of the reference objects are the input to the technical investigation, they act as control variables for many threshold values ​​of the sensor data quality factors. Table 1 shows the preliminary data quality factors for an example reference object as well as the resulting threshold values ​​for multibeam data quality factors, which must be defined before a survey can begin. Some quality factors in Table 1 have already been agreed during expert discussions (green),

while others are still under discussion (white). Detailed tables of data quality factors for all sensors considered so far are available on the BASTA project website.

Practical application

Figure 2 shows an example of a multibeam dataset from the German landfill site of Kolberger Heide and a subsequent AUV camera survey. Several different UXO objects can be identified in multibeam data, but how do you know if all UXO objects on the seabed have been detected, or if some smaller objects have been missed? This question is particularly difficult to answer for datasets that cover large areas with varying water depths and seabed conditions. However, defining well-defined reference object quality factors and sensor data quality factors can help answer this question. Figure 3 illustrates the data quality factors calculated on the same real multibeam dataset for two UXO objects of different sizes. The quality factors are calculated against the cut-off values ​​defined in Table 1. The dataset seems generally sufficient for the detection of an air bomb (left column: GP 550 lb M64). On the other hand, the calculated footprints indicate that the smaller object (right column: 155mm BL Mark VII shell) would likely be missed in large parts of the study area (please note that this working example is intended to illustrate the idea). Similar threshold values ​​can be calculated for the other sensors listed in the workflows. Once the data quality factors are finalized, the calculation presented in this article will be available as features through AmuCad.org and TrueOcean.io.

Conclusion

A well-defined workflow and commonly accepted data quality factors for geophysical survey data can improve project transparency for UXO surveys, as shown in the example. For complex data sets in particular, which include many sensors that must be understood by multiple parties involved in a project, these tips can facilitate communication between stakeholders. Since acceptance by industry experts is crucial for the future application of the data quality factors presented in this article, their definition is facilitated by a stakeholder-driven process. The results presented here are preliminary and will be finalized in a discussion workshop to be organized during Kiel Munition Clearance Week in September 2021.

The references

Frey, Torsten (2020): Quality guideline for explosive ordnance disposal at sea. 1^st Editing. Berlin, Zurich, Vienna: Beuth Verlag GmbH.

OHI (2020): OHI S-44 Standards for Hydrographic Surveys, 6^e Edition, Monaco: International Hydrographic Organization.

IOGP (2009): Guidelines for Conducting Offshore Drilling Hazard Investigations, Version 2.0, London: International Association of Oil and Gas Producers.

NOAA (2019): Hydrographic Survey Specifications and Deliverables, National Oceanic and Atmospheric Administration.

OWA (2020): Geophysical Survey Guidelines for UXOs and Rocks Supporting Cable Installation, Offshore Wind Accelerator.