Assimilating the Assets

March 1, 2007
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Collecting data on a newly constructed pipeline.


When the third largest independent producer of natural gas in the United States acquires the assets of a century-old oil and gas exploration and production company, the development of an integrated GIS becomes both a priority and a challenge. This was the case with Chesapeake Energy LLC and Columbia Natural Resources LLC (CNR) in late 2005. CNR’s mapping system needed to be integrated into Chesapeake’s application systems and databases. As a professional surveyor employed by the company, I was given the opportunity to assist in coordinating this effort.

Columbia Natural Resources, now renamed Chesapeake Energy Eastern Division, owns more than 8,500 producing wells; a lease hold of approximately 4 million acres; and 7,500 miles of pipelines and associated facilities, such as measurement stations, valve settings, fluid extraction devices and tanks. In attempts to help manage these assets, CNR began a mapping conversion project about 20 years ago to integrate all company paper maps into one central CADD system. Since the company’s assets included several predecessor companies that had been acquired over time, the maps and data varied in virtually every respect, including accuracy, mapping datums and symbology standards. The project was completed in 1993 and maintained thereafter, accommodating both internal growth and growth through various acquisitions to reflect the company’s current assets. The complete CADD mapping system enabled the company to maintain and publish maps much more efficiently. By progressing from paper to digital maps, each map feature and asset type could be maintained within unique CADD layers, which allowed for custom map publication by selecting multiple layers of data based on users’ needs.

As progressive as CNR’s new system was, its limitations became apparent over time; most notable were compatibility issues with the graphic CADD data and existing databases of related features. For example, the mapping system included a layer of the company’s well locations, but users couldn’t access it together with the valuable well data that was available in the well database system. Overall, the CADD system wasn’t integrated with the available database resources to make an efficient GIS. There was a huge disconnect. A solution was needed.



The GIS Solution

A few years ago, CNR explored the possibilities of using this valuable CADD data to develop a GIS. Although everyone involved recognized the value of such a system, the timing wasn’t right because of budget constraints and an impending change of company ownership at the time.

With the acquisition by Chesapeake Energy, the time to convert to GIS had come. Creating a complete and accurate GIS resource for the combined divisions was essential. Luckily for the new Eastern Division, the parent Chesapeake Energy had already implemented GIS on the ESRI (Redlands,Calif.) ArcGIS platform. With the guidance of an ESRI consulting team and the GIS staff in Chesapeake Energy’s headquarters office in Oklahoma City, our company is now at the threshold of implementing GIS after beginning the conversion of CADD data some eight months ago. But it hasn’t been without several challenges along the way.



John Collette, pipeline foreman for Chesapeake Energy’s Corbin, Ky. Field Office, collects data with a Magellan MobileMapper CE.

Challenges to Overcome

The greatest challenge for the integration was the sheer volume of CADD data that first had to be converted to the ESRI platform. Our GIS team, including representatives from various departments we serve, including Geology, Land and Pipeline Facilities, was forced to assess which types of graphic data could be linked to existing company databases. The problem was that all of the data to build the GIS foundation came solely from a graphic system that contained no attribute data. By grouping the data into three major categories--lease parcels, wells and pipelines--it was obvious that implementing GIS would yield immediate benefits for the lease and well categories because of the available databases that could be used with them.

However, the pipeline category and associated field facilities presented a major challenge to the team. The only available source of pipeline data to create a complete and accurate GIS was a graphic representation of a 7,500-mile pipeline system. What did not exist was the critical component of a system database to correlate with the graphic data. Furthermore, the current and new aggressive expansion and acquisition of properties, wells and associated pipeline construction added a tremendous new burden to the task. Our dilemma: how to efficiently collect accurate pipeline data while simultaneously capturing all related attribute data to build an intelligent model of the pipeline system. We needed a solution that would handle not just very substantial new pipeline construction, but would also populate the system with all existing facilities over time.



Challenges to Overcome

The greatest challenge for the integration was the sheer volume of CADD data that first had to be converted to the ESRI platform. Our GIS team, including representatives from various departments we serve, including Geology, Land and Pipeline Facilities, was forced to assess which types of graphic data could be linked to existing company databases. The problem was that all of the data to build the GIS foundation came solely from a graphic system that contained no attribute data. By grouping the data into three major categories--lease parcels, wells and pipelines--it was obvious that implementing GIS would yield immediate benefits for the lease and well categories because of the available databases that could be used with them.

However, the pipeline category and associated field facilities presented a major challenge to the team. The only available source of pipeline data to create a complete and accurate GIS was a graphic representation of a 7,500-mile pipeline system. What did not exist was the critical component of a system database to correlate with the graphic data. Furthermore, the current and new aggressive expansion and acquisition of properties, wells and associated pipeline construction added a tremendous new burden to the task. Our dilemma: how to efficiently collect accurate pipeline data while simultaneously capturing all related attribute data to build an intelligent model of the pipeline system. We needed a solution that would handle not just very substantial new pipeline construction, but would also populate the system with all existing facilities over time.



At a well site, Chesapeake Energy’s Collette collects a variety of features with the Magellan MobileMapper CE, including well head, tank and separator.

The Tool for the Job

To implement the GIS, we needed to update and identify the locations of existing field assets and capture new ones. Once the GIS was established, we would need to disseminate the information for use in the field. Since the tasks of capturing and using data in the field would be undertaken by dozens of personnel from different specialties, it was important that the GPS field data collectors we chose have a short learning curve and low cost. Additionally, the receivers needed to be submeter accurate; provide measurements in real time; and be able to upload and download standard and proprietary road and topo maps, proprietary Shape files of property lines, and previously recorded facility locations and attributes. After evaluating the products on the market, we chose the Magellan (San Dimas, Calif.) MobileMapper CE GPS field receiver and data collector.

The MobileMapper CE offers an open platform on which any number of onboard software programs can be used. We elected to load SOLO Field software (Tripod Data Systems, Corvallis, Ore.) for its ease of use.

We decided at least 100 MobileMapper CE units were required due to the volume of data we needed to capture and because of the broad and growing operating territory. To date, more than 50 units have been deployed by various Chesapeake field personnel. The number of units utilized also meant that our relatively small GIS staff would be inundated with enormous amounts of data coming in from the field. We wondered how the small staff would cope with data management and maintaining data integrity as we organized, validated and assembled the central GIS repository.



The Problem that Wasn't

In addressing these concerns, we first had to visualize what the final product should be and then create a GIS geo-database to capture all the required pipeline attributes, essentially creating an empty database and working backward to populate it. This process required the involvement of several of the company’s business units, including Field Operations, Pipeline/Production Engineering and Regulatory Compliance, to ensure all required data would be captured. Once that was done, an onboard feature table was created for the MobileMapper CE that allows each user to easily record all necessary pipeline and facility data along with the attribute data that is required to populate the geo-database. If all of the MobileMapper units use the correct feature table, the data management and data integrity issues are more easily controlled. In fact, large volumes of field data can be validated and published to the system so efficiently at the office level that it doesn’t appear to matter if data is being received from 50 units or 500 units.

Another source of concern early on in the project was how quickly field observers could learn to use the units effectively. The user friendliness of the MobileMapper CE has been a big help in this area. While at first glance the MobileMapper CE may appear daunting to some users, our experience is that this fear is quickly overcome during minimal training. Our field technicians report that the MobileMapper CE and the menu-driven SoloField software and feature table are easy to use and keep errors to a minimum. These factors are helping our team to be right where we want to be in the project.

GIS data is already flowing back into the field. Mapping data based on the GIS is being deployed back into the field for use on field PCs and the MobileMapper CEs. Returned data is provided as Shape files, which enable field groups to place and manage the data into their own project applications as they wish. Because each of the MobileMapper CEs contains a 1-gigabyte SD card, we can upload all of the updated information, including topos and existing Shape files, right on the MobileMappers for real-time use in the field. This enables, for example, a field engineer out on a new lease to know in real time where the property boundaries are in relation to subterranean features.

Management is also pleased; they are now getting automated daily updates on what specifics have been accomplished, what percentage of work has been done and what still has to be completed.

With a project of this size and scope, there naturally were some concerns. We wondered how effective the new technology would be be in the hands of the many diverse people and departments involved. We had little to worry about; our tools were clearly designed for a project like Chesapeake Energy’s. Today the company is well on its way to integrating the many diverse and dynamic data elements of a major natural resource utility.

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