The American Oil and Gas Reporter
Solution Optimizes Asset Management: By Christoper Colvin and Tim Supple
LAFAYETTE, LA.–Most oil and gas exploration investor presentations contain a page describing “total resource potential.” This shows the investor the value of the lands under lease, but not yet drilled. Such presentations go on to break down the resource potential into geological areas (Marcellus, Haynesville, Bakken, etc.), and then into more specific areas by “tracts of leased” acreage and “percentage of developed and nondeveloped” acreage.
After five years of unprecedented lease acquisitions, the focus has changed. Companies now are emphasizing turning “potential” into “proved and producing.” However, several challenges exist, including computing undeveloped acreage and developed acreage for asset evaluation, and the expiration of leases before they can be turned into “developed acreage,” thereby saving the most valuable assets.
In order to compute both developed/producing and resource potential/undeveloped lands, management needs the land department to be able to calculate and demonstrate the company’s leasehold positions by geological area, by individual tract, and by producing/nonproducing status. Furthermore, identifying the most vulnerable assets (nonproducing tracts with pending expiration dates) has become too complicated for Excel™ spreadsheets and normal geographic information systems mapping.
This is where real-time data–with real-time GIS analytics–becomes an invaluable management system. Denverbased High Plains Energy, a privately held, midtier independent oil and gas company, has been successfully leveraging such a system to prioritize its assets for drilling and production operations.
The advancements of new database configurations and integrating spatial query mapping into the functionality of newer systems have given oil and gas companies innovative solutions necessary for advanced management functionality.
Companies need to “see” (map) where they own acreage, and have access to a report (database) detailing how much they own and where, and not only in terms of gross acres, net acres or even net working interest acres. For High Plains Energy, landmen need to know what the net revenue interest is relative to the working interest by geological area, specific sand or formation, unit or well basis, and on specific tracts of land.
Simplifying Leasing Decisions
High Plains is mastering a system that can handle the necessary computations. Sometimes, the questions are not very simple, but the way in which the company gets answers has become much easier and the technology is making leasing-related decision making much simpler. Once the information is loaded, queries are made automatically and in real time. The workload on the company’s staff is reduced substantially at every level, from field lease acquisition to asset evaluation.
The functionality of this integration is based on the simple premise that any and all tracts of land under lease exist in a fixed location, and that the location is identifiable both in the legal description used in the database, and in its geographical coordinate system location in mapping. Neither of these is variable on any given tract. By using the link already created between the tract of land and the geographical coordinate location in mapping software, these varied locations are now one and the same.
Any tract can be identified both in terms of its legal description and/or its geographical coordinates. By identifying tract(s) of land by spatial selection in mapping (x-y coordinates location with the legal description) and sending that list to the database, the operator creates the first step in selecting “where.” The database can run preselected filters, or the operator can select filters for reports and provide visual map attributes reflecting values for each tract.
Integrating the database with mapping allows the operator to create maps from data or data from maps, or any combination of the two. The analytics, reports or maps that can be generated by this new methodology are infinite, automatic or user-defined. In other words, they are limited only to the data available and the operator’s imagination.
Real-time, tract-based land management gives all stakeholders access to the project management process. The technology standardizes data collection, makes lease/contract preparation and permit acquisition more efficient, enables proactive management of brokers, aids in assessing project performance and the management of day-to-day operations, and provides complete online access to all company projects along with maps and reports to increase efficiency while eliminating wasteful duplication of effort.
The following examples illustrate how spatial queries make data and reports more actionable. Figure 1 shows a Chesapeake Energy Corporation presentation to investors of its “major assets” by geological area. Notice that every geological area is outlined or highlighted. That outline creates an identification to provide the ability to create a “spatial query,” which reports to the database all tracts within that “space.” From that spatial query, the database automatically updates acreage and cost.
Figure 2 of the Haynesville Shale geologic area illustrates the holdings of different companies on a tract-by-tract basis. Figure 3 displays individual proration units as set up by the Louisiana commissioner of conservation. This outline creates a special identifier that permits selection of only those tracts within that spatial query. Also visible are the well locations and horizontal extensions of the well bores. These points and lines create new identifiers for spatial query.
Finally, by zooming into the individual tract of land and its outline, the tract’s individual identifier and spatial query are visible. This is the most important identifier; nothing else will function without it. That tract of land is linked to a lease, and that lease is linked to all the data associated with the tract. By identifying the tract(s) through spatial query, any report–including a corresponding map–can be run at any time.
Other advantages of new database configurations and integrating spatial queries abound. Sometimes a tract may extend beyond the proration unit, or there may be another tract on the same lease with the “proration unit tract.” The outline of the proration units, combined with the producing status of the well, now instructs the map to generate an acreage number for both developed and undeveloped acreage, and to send that information to a data field in the database.
Integrated Database, Mapping
And it does all this automatically by running an automatic perimeter measurement of the portion of the tract within the proration unit. This integration of database and mapping functionality allows the map to generate the “developed acreage” amount and store it as “data” for the database. By simply allowing the database to subtract the developed acreage from the tract acreage, the operator has both developed and undeveloped acreage figures.
In this scenario, the oil and gas company can know which developed lands and lease(s) cover its interest. The data-base can calculate by net acres, net revenue interest and working interest on a tract-by-tract basis. Then it is simply a matter of selecting the spatial query the user wants by tract, unit, well, section, township, geographical outline or geological area, or creating a new one.
Because the operator can preset and customize these analytics by simply creating any spatial identifier and adding other data filters such as sand, depth or formation, developed and/or nondeveloped, any report or map becomes automatic on request.
Figure 4 shows additional uses for management, particularly the ability to use the data to create the map and then use a spatial query to create reports from the map. An operating company may want to know where it has leases expiring over the next year. By running analytics from the map, data can be brought in, such as expiration dates. Attributes can be automatically created (expiration by month) and the expiration map can be published.
It then becomes possible to go back and create a spatial query by highlighting the desired area, and running reports on only those tracts on which leases are set to expire. Other desired filters can be added. Reports can be run by selecting any data to create the map. Then a given area on the map can be chosen and reports run based on those attributes, with selected data filters.
Another example of this powerful method is the ability to view “future” events. For example, an operator may have leases with vertical Pugh clauses, where the company could lose all rights below the deepest producing formations, or above production formations, or another condition that a lease contains. Analytics can be run by such contract conditions, and a course of action can be determined. The area can be selected to generate a report that provides information on those particular tracts, leases, owners and/or conditions.
Once various data figures are determined (such as those for gross acres, net acres, net working interest, net revenue interest and expiration schedules), reserve engineers can begin to apply recovery factors, well cost factors and timelines for development. All can be coordinated with additional leasing or acreage acquisition instructions.
The convergence of this interaction has only just begun. Even now, data and mapping from other sources can be integrated and used. Figure 5 illustrates this convergence with DrillingInfo® lease data. When data are obtained from sources with Web services, it is no longer necessary to copy the maps or the data from one platform or source to the other. Data and mapping are shared across platforms for use based on what the operator needs or wants to pull into his view.
Operators simply subscribe to the information source they want as they need it, and pull the information into the base system. The system becomes a uniform environment for performing the work; a converging point where any relevant layer can be pulled in to see the relationships between one asset and another.
One of the most powerful aspects of the real-time lease acquisition management is the seamlessness of the technology. Landmen are collecting the data anyway, and all the information is coming in from leasing agents in the field. The Web-based technology provides the capabilities to allow them to process the data they already have so the data can be in one place to manage the business more efficiently. By so doing, oil and gas company land departments are able to handle the same workload for less cost while making more informed and timelier leasing decisions.
Christopher Colvin is a landman at High Plains Energy in Denver, where he assists in overseeing lease acquisition and developing the company’s land strategy. Colvin began his career at Acadian Land Services more than 10 years ago. A member of the Denver Association of Professional Landmen, he holds a master’s in global energy management from the University of Colorado at Denver.
Tim Supple is president of iLandMan, the provider of the lease acquisition and land asset management software deployed in High Plains Energy’s operations. Based in Lafayette, La., Supple has 30 years of experience as a practicing landman. He was instrumental in developing iLandMan, and is especially involved with the company’s mapping proficiencies. A landman from 1978 to 2000, assisting oil and gas companies such as Chevron, Exxon and Apache, Supple also previously ran a small exploration, drilling and production operation. He holds a B.S. in history from Louisiana State University.
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