Field automation means fewer failures, less downtime and more efficient use of personnel.

XTO Energy is a domestic producer with a history of acquiring properties where technology can be used to increase profitability and extend the life of the reservoir. XTO optimizes assets through drilling, workovers and cost reductions. Since operating costs are a contributing factor to the cost per bbl of production, minimizing operating costs reduces the production cost per bbl. Production cost per bbl is defined as field overhead expense coupled with operating costs.

An integrated system

Each morning, the XTO well specialist reviews data scanned from producing wells fitted with intelligent controllers to make informed decisions about which wells need attention that day. He then prioritizes an action plan and dispatches the appropriate personnel and resources to these high-priority wells using knowledge based on data received from rod pump controllers and analyzed with the desktop software system. This process reduces the time to troubleshoot a problem well and significantly reduces mean time to repair.

For example, if a well consistently pumps off and cycles several times per day, but suddenly starts running continuously without pumping off, the production optimization system immediately identifies the change. This condition usually means that the fluid level is remaining at a high level, which could indicate a change in reservoir behavior, or more likely, a tubing leak. Finding and repairing the leak minimizes deferred production and eliminates the excess cost of pumping an inefficient well.

A tale of two fields

XTO uses production optimization systems in two West Texas fields, the Prentice North East Unit and the Cornell Unit. XTO assumed operations of the Prentice field in 1994. Today, the field is equipped with rod pump controllers manufactured by eProduction Solutions and a supervisory control and data acquisition (SCADA) software system. The Prentice field currently produces 3,200 b/d of oil and 65,000 b/d of water with an average water cut of 95%. Currently, there are 149 rod pumped wells and 53 ESP wells. The average well depth is 6,900 ft (2,104 m).

XTO took over operations of the Cornell field in August 2000. All wells were equipped with rod pump controllers, but none of the controllers were in service. After repairing and re-commissioning the controllers, an automation/optimization software system from Case Services was installed. By the end of 2002, 67 wells were automated. The Cornell field produces 1,600 b/d of oil and 15,500 b/d of water with an average water cut of 91%. Currently, there are 67 rod pumped wells and 1 ESP well. The average well depth is 5,100 ft (1,555 m).

Well optimization benefits

XTO realized savings in the following ways.

Reduction in well failures. The combination of intelligent hardware control at the well site and software analysis at the desktop provides a system that allows the operator to fine tune well operations. By using the information provided by the system (e.g. surface cards, downhole cards, run-times, and gear box torque), the operator can monitor, analyze and control the operation of each well.

The routine review of the well's operating parameters assures that the well is producing optimally and does not exceed the stress limits of the lifting system. This leads to a substantial reduction in the average failure rate. The "management by exception" feature of the software further reduces well failures by predicting problems before they occur. The operator sets warning limits that can indicate whether a particular point is out of range or dangerously high (exceptions). Wells with exceptions are displayed in a separate window to flag them for immediate attention.

Reduced down time. By using an integrated decision management system, the operator is able to immediately determine when a well is down. When wells do fail, the operator is able to send a crew to the well armed with knowledge from recorded well history. From this information, the repair crew has an accurate idea of the problem before traveling to the well. This allows them to bring the necessary resources to repair the problem in one trip.

More efficient use of personnel. By identifying real and potential problems from the office, operators have reduced the need to send employees out to monitor wells. Now, rather than having personnel out searching for problems, the company is able to maximize efficiency by focusing on current problems and preventing future problems.

Utility cost reduction. Studies have shown that using rod pump controllers can reduce electrical consumption by as much as 40%. XTO couples rod pump controller technology with optimization software to gain maximum savings.

The controller saves electrical costs by optimizing run time while maintaining or sometimes increasing production. When operated on a timer, a well can be pumped off but still be running, using electricity to operate a pump that is yielding no fluid. The rod pump controller senses pump-off and shuts the pump down until the wellbore fluid level rises. The user can analyze the well and make changes to pump parameters remotely so that the well runs the optimum amount of time.

The cost benefits are illustrated by the decrease in rod, pump and tubing failures.
Data, taken directly from field records, shows the costs per repair based on a constant cost factor derived from field experience. A significant portion of the reduction in failure costs was due to the implementation of the basic SCADA software system and the accelerated savings from the automation/
optimization system. Even though the total number of wells increased, the number of well failures decreased, leading to a significant decrease in failure rate per well.

Intangible benefits

While there is no hard data to quantify the results, anecdotal evidence indicates that in addition to the savings from failure reduction, general operating costs savings were experienced.

Water injection management efficiencies. By using injection-monitoring hardware at the well site and injection software at the desktop, the operator knows almost immediately when water break-through occurs and can pinpoint the source. Such knowledge allows for optimum reservoir injection management.
Meeting injection targets is enhanced by the quick identification of plugged injection meters. With this knowledge, meters are cleaned in a timely manner and injection goals can be achieved on schedule.
In one example, injection monitoring was used to diagnose an unsuccessful new well completion. The completion resulted in 100% water production. Logs were unable to determine the source of the water. Monitoring of offset injectors suggested the problem was due to communication behind pipe to an upper zone that is flooded in the offset injectors. A workover to repair the well is being evaluated.

Chemical treatment management. By monitoring the area of the dynamometer card, the well analyst is able to determine when friction is building up in the pump. Comparing the cards before, during and after chemical treatments allows the analyst to determine the optimum time to treat the well, rather than treating the well on a scheduled basis.

Conclusion

After making a calculated investment in technology and reevaluating how it could positively impact the operational organization, profitability of these two XTO fields dramatically increased. Consequently, they have extended economic life through substantial savings in operating costs. While automation and optimization systems are not by themselves the answer to extending reservoir life, the key lies in automation technology that is exploited by individuals who understand the value of daily analysis.
XTO chose to supply the tools to reduce operating expense and extend reservoir life. The significant improvements derived from that cost reduction will allow the company to produce oil long after it would have, had it chosen to continue operating its assets using traditional methods.

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