GIS for environmental data management and analysis in E&P
At Exprodat we recently carried out a review of GIS use in the environmental side of the oil and gas business with the participation of some of our clients. The results show that awareness of how GIS can support environmental data management and environmental analysis workflows is still at an early stage in many of the companies we reviewed . GIS is often perceived by environmental teams as the “territory” of a few specialists, who may not actually sit within these teams.
Given the outcome of our study, I thought it would be worth showing a typical environmental workflow, to demonstrate how ArcGIS can be used to support analysis tasks effectively and quickly.
Environmental and Seabed Constraints Analysis
Let’s assume the following scenario: the permitting team within the HSE department needs to understand the environmental and seabed constraints that affect a given well location. Although in my scenario the location of the new well is offshore, the same analysis principle can be applied to any onshore location as well as other exploration activities such as planning a new seismic survey acquisition campaign.
For this new development the permitting manager needs to answer a few simple questions:
- 1) Is the location of the proposed well within environmental protection and other surface and/or seabed constrained areas?
- 2) What is the minimum and maximum distance from the proposed well location to any constrained areas?
For my example I chose to focus on the Baltic Sea, mainly due to the availability of public data sources suitable for the analysis. Figure 1 below shows the area of interest; data has been downloaded from the HELCOM (see note 1) map and data service website. Shipping lanes and wind farm permit datasets have been made up arbitrarily.
Figure 1 – Study area used in my test
A detailed map of the existing seabed and environmental constraints is shown in Figure 2 where the location of the proposed new well is also indicated. All my data is in vector format; as you can see there is a variety of constraints affecting the proposed well location (see note 2). The presence of overlapping polygons was a factor which had to be taken into account when implementing the constraint analysis workflow, as discussed below.
Figure 2 – Constraints for the proposed drilling location
I made the assumption that the permitting team only has access to ArcView and Spatial Analyst (see note 3).
Model Builder for constraint analysis
For my constraint analysis workflow I used the ArcGIS Model Builder, in order to provide a portable and reusable tool for constraint analysis. This could then be shared among users within the permitting team or used for similar analyses elsewhere.
The model implements the following sequence of logical steps:
- Classify constraint features based on the location of the proposed well with respect to the boundaries of the corresponding polygons (features classified as “within” or “outside”). This task is accomplished by using the Spatial Join tool.
- Define the study area (analysis carried out only for those features which are at a significant distance from the proposed drilling location) and use the Euclidean Distance tool to generate a grid of distance values from the well location within the study area (see Figure 3 below).
- Calculate the relevant statistical values (min and max distances to the boundaries) for features where the proposed location falls “outside” the polygonal boundary of the existing constraints using the Zonal Statistics as Table tool.
Figure 3 – Use of the Euclidean Distance and the Zonal Statistics as Table tool to derive distances for polygons classified as “outside”
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Calculate the relevant statistical values (min and max distances to the boundaries) for features where the proposed location falls “within” the polygonal boundary of the existing constraints by converting these features from polygon to polylines (I did this by using the “Write Features to Text File” script available in the Sample toolbox at 9.3.1.). Then convert the output back to a polyline feature class (by using a modified version of the “Create Features from Text” script available in the same toolbox).
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Finally follow a similar process as described above to extract distances to the boundaries of constraints (Figure 4).
Figure 4 – Convert polygon features to polylines to derive distances for features classified as “within”
Results
The environmental and seabed constraint map is shown in Figure 5. Constraints within the output layer have been symbolised based on distance from the proposed drilling location and the closest features have been labelled based on their attribute (constraint type).
The attribute table for the output layer reports the minimum and maximum distances from the border of the polygonal feature.
In my scenario the constraint analysis allowed me to quickly extract the following information that needs to be accounted for when planning the well location:
- The proposed location falls within a shipping lane, a chemical munitions dumpsite and a geo-hazard area (“within polygons”).
- Minimum distance from boundaries of the “within” polygons varies from about 900 m and up to 5000 m.
- Various constraints are classified as “outside” polygons. The proposed well falls outside these areas.
- Minimum distance from boundaries of the “outside” polygons varies from about 5000 to up to several kilometres.
Figure 5 – Environmental and seabed constraints analysis map
Conclusions
The constraint analysis workflow provides information which is useful in the early stages of the planning and development process, where data at a regional scale is used to support the environmental permitting process.
The model would allow a permitting team to analyse suggested locations for exploration and development activities (such as drilling and seismic surveys) with respect to the environmental and physical constraints at both regional and local level. The map shown in Figure 5 can easily be integrated into an environmental impact report or any other permitting document required in an application procedure.
In summary, I hope that I have shown how in an oil and gas organisation GIS technology can provide decision support beyond the geoscientists sitting within the Exploration department. As our review demonstrated, the key element is to communicate the value of GIS across an organisation, increasing awareness at both the technical as well as the managerial level.
Posted by Paola Peroni, Senior GIS Consultant
Note 1: The Helsinki Commission (HELCOM) works to protect the marine environment of the Baltic Sea from all sources of pollution through intergovernmental cooperation between Denmark, Estonia, the European Community, Finland, Germany, Latvia, Lithuania, Poland, Russia and Sweden. Some of the data made available by HELCOM and used within the context of this blog has been partially modified to better suit the scope of my test.
Note 2: The well location discussed here is arbitrary and unrelated to any real world development in the area.
Note 3: ArcGIS provides a Proximity Analysis toolbox which contains tools that can be used for calculating the minimum distance between a point and polygon features. However, the tools needed to accomplish the type of analysis discussed here (such as the “Near” tool) are only available in ArcInfo.