Site Suitability Assessment for Hydraulic Fracturing Operations

Combining State Regulations with Business Best Practice

The discovery of vast amounts of natural gas reserves in the United States, combined with new extraction techniques, has caused a significant increase in the number of wells being drilled and operated around the country. Along with the economic and homeland security benefits of developing this resource comes an increased risk of adverse affects on fresh water supplies that communities and other industries rely on. In response to this risk, individual states have adopted strict laws that govern the way that oil and gas companies can extract natural gas while protecting the integrity of the local waterways and aquifers.

While laws that regulate natural gas development vary from state to state, they have similar constructs in that they limit the distances from housing and water sources that drilling and extraction operations can occur. Geospatial analysis can be used not only to derive maps that identify areas outside of certain buffers as defined by the state, but also to select sites that are a better fit for drilling based on the requirements of the company. The ability to quickly narrow down locations for a new site based on state regulations and business best practices using accurate data analysis reduces the time and resources needed to identify the best potential sites while protecting the region's natural resources.

Businesses are responsible for knowing the regulations, both federal and state, that apply to their drill site and face heavy fines for any violation of these regulations. In 2012 the West Virginia University College of Law authored a whitepaper that examined the different hydraulic fracturing regulatory approaches of New York, Ohio, Pennsylvania, and West Virginia. These states sit on top of the largest natural gas reserve in the United States, known as the Marcellus Formation, and have adopted similar yet differing regulations. The paper examines how the different state regulations affect the industry and highlights this region as an evolving case study in state-defined environmental law. It also summarizes each of these state's regulatory requirements nicely, providing information on setback distances and other relevant data about how a drill site can be developed, which will be used as guidance for this case study .

Site Suitability Assessment - Petersburg, PA

Geospatial information such as satellite imagery and LiDAR data can be extremely useful in the identification of ideal drill site locations. To explore the usefulness of geospatial information in the identification of suitable drill sites, data was collected over Petersburg, Pennsylvania, a small town located on the Marcellus formation in central PA. A Light Detection and Ranging (LiDAR) data set over the area with an average of 15 points per meter squared was acquired from the National Science Foundation's Open Topography website (figure 1).

 

Figure 1 - A 3D LiDAR scene showing extracted buildings and elevation over Petersburg, PA

 

A high resolution Digital Elevation Model (DEM) was extracted from the point cloud using ENVI LiDAR, as well as a perimeter shapefile for each of the buildings in the scene. The elevation data was then used to create a layer showing the slope of terrain across the area. This slope data provides useful information that drilling operations can use to locate areas that are within a desired slope range. Leveling earth that has a high slope is costly, and it was assumed that drillers would be looking for areas consisting of less than five degrees of slope. The building shapefiles extracted from the LiDAR provide a good layer that can be buffered to ensure that the drill location meets state setback requirements.

Shapefile data from the US Census Bureau depicting local waterways, roads, and railways was added into the map to gain a better context of the area in general, as well as to allow for buffers to be created around the water bodies that conformed to the state regulations. All of this information was gathered into ENVI to perform the appropriate analysis (figure 2).

 

Figure 2 - Rivers, roads, and LiDAR-extracted buildings overlaid on a derived slope model

 

In the West Virginia University College of Law whitepaper, the Pennsylvania drilling setback laws are summarized as follows: "a new vertical well bore shall not be within 500 feet of buildings or water wells, within 1,000 feet of water resources used by purveyors, or within 300 feet from streams, springs, wetlands, and other water bodies".1 No water resources used by purveyors were found in the region, which reduced the setback regulations to 300 feet from water bodies and 500 feet from buildings. These buffer distances were then applied to the waterways and buildings shapefiles, highlighting areas that were off limits to the search according to state regulations.

The slope dataset was sliced to identify only areas that consisted of a slope of five degrees or less. Since these areas can be clusters of low slope with small patches of moderately higher slope terrain speckled in, a clump function was performed to ignore small patches of higher slope terrain under the assumption that minor leveling of the land was acceptable. In other areas, low slope land can consist of individual spots within areas of higher slope, so a sieve function was performed to identify only those locations that had an area of three and a half acres which, according to industry estimates, is the average size of a multi-well pad for the drilling and fracturing phase of operations. The map shown in figure 3 shows the waterways in blue, building shapefiles in red, the combined waterway and building buffers in purple, and areas of low slope that adhere to the three and a half acre minimum in yellow.

 

Figure 3 - Waterway and building buffers and suitable drilling locations

 

Generating a Final Product

After identifying both the buffered areas and the areas that consisted of acceptable slope that covered at least three and a half acres, a mask was performed to create a layer that showed only the locations that would be suitable for drilling. A final map product was then created to depict all of the analysis layers in a single place, which could then be distributed to executives, state or federal authorities, or to exploration teams going into the field to conduct further suitability assessment on the ground (figure 4).

 

Figure 4 - Final map showing suitable drilling locations in the study area

 

Further Considerations

There are several things to consider during the preparation and analysis of geospatial data for site suitability assessment. The first thing to consider is the spatial resolution of your data. The LiDAR dataset that was used in this example had a very dense point spacing with an average of 15 points per meter squared, which meant that ENVI LiDAR was able to extract a very high resolution DEM from the Petersburg point cloud. Many freely available LiDAR datasets struggle to have more than a point or two per m2. Point clouds and elevation data that lack the proper accuracy to perform meaningful analysis can skew results and feed bad information into your decision making process. Always make sure that the data you use is spatially accurate so you get precise results from your analysis.

Another consideration is the attribute information for your shapefiles. The shapefiles that were acquired from the US Census Bureau had some errors where certain features were incorrectly attributed (i.e. roads were classified as waterways), which could have severely altered the area that buffers would cover. Some manual edits were performed to the attributes of those features to ensure they were identified correctly. Ensuring the fidelity of your shapefile attributes avoids severe errors created by basing your site suitability on incorrect buffers.

Finally, and this goes for any geospatial project you work on, make sure that all of your datasets are in the same projection. Variable projections can have major effects on the placement of items or datasets on the map, and analysis run on data with different projections is by definition inaccurate.

Summary

Geospatial data analysis allows oil and gas companies to conduct remote site suitability assessment for drilling operations. Businesses must take into account the state and federal regulations that are in effect for the area they are prospecting in order to protect local resources and avoid fines. Geospatial data can be used to determine suitable sites based upon industry best practices as well, incorporating requirements such as slope or plot size into the search for the best site.

Analysis for site suitability was conducted over the areas just North and East of Petersburg, a small town located on the Marcellus Formation in the state of Pennsylvania. LiDAR data was used to extract high resolution elevation data to assess the slope in the area, as well as building footprints in order to create a 500 meter buffer around them to meet state regulations. Waterway shapefiles were also retrieved from the Census Bureau in order to buffer them at 300 meters per state regulations. Once the buffers and suitable slope areas were found, the buffered areas were removed from the slope data, and a clump and sieve function was performed to identify areas that met the conditions of being outside the state regulated buffer zones and consisting of an area of at least three and a half acres with slopes of less than 5 degrees. The complete depiction of suitable areas was then ported over to a map that could be shared within the business or with regulating authorities as needed.

Finally, there are some considerations to take into account during the selection and analysis of data for drill-site suitability, or any other geospatial analysis. Understanding the effects of your data's spatial accuracy can help to ensure you are conducting analysis that is precise enough to deliver the answers you need. Accurate shapefile attributes are another important factor when conducting this type of analysis. Poorly attributed data can cause buffers to be applied to features that do not represent what they are attributed as. This causes non-buffered zones to be buffered or vice-versa, resulting in an inaccurate depiction of available sites. Data projections must also all be consistent in order for analysis to be correct. Analyzing data that are in different projections can cause severe errors that undermine the validity of your project.

Naturally there are other considerations and analyses to take into account when planning and executing hydraulic fracturing operations. ENVI provides multi-modal data support and a full suite of geospatial analysis functions that can be used to extract information from remotely sensed data. This information can help businesses conduct oil and gas discovery, drilling, and extraction more confidently and safely.

Sources:

1. "Marcellus Shale Drilling Comparative Whitepaper: The regulatory approaches of New York, Ohio, Pennsylvania, and West Virginia", 2012. Prepared by Travis L. Brannon & Walter C. Shepherd, Research Assistants under the supervision of James M. Van Nostrand, J.D., LL.M., Director. http://energy.law.wvu.edu/r/download/130703

2. www.shale-gas-information-platform.org