Business/economics

Flood Management: Solving Conformance or Sweep Efficiency Problems—Part 3: Solution Performance Analysis

Part 3 of this series looks at the importance of performance analysis and how to generate the economic benefit for solving conformance or sweep efficiency problems. The economic elements of this review are very basic, but they will help you to determine a more-accurate understanding of the true economic benefit.

Data analyst working on business analytics dashboard with charts, metrics and KPI to analyze performance and create insight reports for operations management.
Source: Getty Images.

In Part 1 we covered the basic outline for conformance engineering practices with a focus on understanding the problem and how that impacts success rate. In Part 2 our focus was on making a connection between the problem type and the solution options available for dealing with conformance problems.

Part 3 looks at the importance of performance analysis and how to generate the economic benefit for solving conformance or sweep efficiency problems. The economic elements of this review are very basic, but they will help you to generate a more accurate understanding of the true economic benefit.

Job or Treatment Performance Analysis

As discussed in Part 1, we often misunderstand the full or true nature of the conformance problem we are dealing with. This misunderstanding can often be corrected if we take a careful look at the post solution execution information.

In SPE 103044, we discussed how the first two solutions applied in the Permian Basin Anton Irish field which pumped 8,000 bbl of high-molecular-weight crosslinked gel, followed by 2,000 bbl of nitrified cement, only resulted in the maximum net pressure increase during pumping of 150 psi. This taught us that the features we were treating were much larger and more prolific than we originally expected. From this we improved the strength of our treatments and at the same time reduced costs by redesigning several elements of the solution process.

Another great example of utilizing treatment performance analysis was shown in SPE 190209 which solved a conformance problem in the offshore Ekofisk field in the North Sea. In this solution, we needed to confirm that we could execute the design without the need for a costly workover or drilling rig. We needed to confirm that we could pump approximately 3,000 bbl of nitrified cement through the existing completion without fear of locking up. Thus, in the planning phase of this solution treatment we pumped a densified gel designed to emulate the pumping of nitrified cement through the existing completion. Fig. 1 shows the pressure responses during that emulated treatment.

pressure responses during an emulated treatment
Fig. 1—The pressure responses during an emulated treatment in the offshore Ekofisk field.
Source: SPE 190209.

This plot compares the bottomhole pressure vs. the surface treating pressure during the period when the densified gel cement emulation fluid was pumped. The pressure scales have been shifted to eliminate the hydrostatic differential while pumping with water at 5.0 bbl/min. This allows us to look at the change in the curves to show the effect of the emulation fluids’ friction effect in the tubulars vs. the effect in the VSC (void space conduit) we were pumping into.

For the friction effect in the tubulars (4.5-in.-diameter with a capacity of about 240 bbl), we looked at the end of the job when we shifted from pumping densified gel to pumping water. Analysis of this section highlighted by the blue-shaded circle in Fig. 1 shows that the net friction pressure effect that was generated while pumping at 5.0 bbl/min with the densified gel in 4.5-in.-diameter tubing was approximately 1,160 psi. We can then compare this to the bottomhole pressure response, which basically represents the friction pressure response for pumping 3,200 bbl of densified gel into the VSC at 5.0 bbl/min was only approximately 500 psi.

We also executed a stepwise rate change in the middle of the treatment that further confirmed these relationships, but the explanation of that effect would take too long to explain. Bottom line, this analysis confirmed the massive character of the VSC, which we suspected, and which gave us complete confidence that we could execute an approximately 3,000-bbl nitrified cement solution for this problem.

Experience with many other cases has revealed important insights on the character of the problem when careful analysis of the solution execution has been conducted. This has allowed the redesign of solutions to generate improved success and more confidence in what is needed to solve these problems.

Analyzing the True Economic Benefit

Now let’s look at a simple way to incorporate a full benefit analysis when solving conformance problems. In many cases generating a complete financial analysis is difficult due to various tax and operating cost considerations, and this analysis does not accurately cover those elements. However, the following method will generate a more complete economic benefit from conformance work that should improve your understanding of the actual benefit realized. This technique or something similar has been used by many major assets in the US.

The terms and system designed below are set up to handle WSO (water shut-off) or GSO (gas shut-off) treatments—including CO2—for oil production wells and/or injection patterns.

This method uses three elements to derive a better estimate of the true economic benefit for a field: Qod (direct rate benefit), Qoid (indirect rate benefit), and the Qoes (operating expense savings).

Direct Rate Benefit: Qod

The first and easiest term to define is Qod. This element is simply the increase or decrease in oil rate that is observed from a well or pattern after a solution is completed.

The equation for this term is Qod = (Qoa – Qoi) or oil rate after solution execution − oil rate before solution execution.

This is only for the well or pattern treated. For injection-well treatments, this includes all affected producers. Generally, this is only for the immediate pattern, but may be modified based on performance. Another distinction between producing-well treatments and injection-well treatments is a time lag. Producer-well treatments generally show a rapid or immediate response to treatment. In injector treatments, the response is often delayed by several months before the full impact is seen at the producers. Thus, with injector treatments, a time lag needs to be applied to the benefit.

Indirect Rate Benefit: Qoid

The second term, Qoid, is a little more difficult to estimate, but is based on trying to estimate the amount of oil increase that can be put through your facility through some optimization method.

For example, if you remove X total bbl of fluid rate from the facility system, you can, to some degree, replace a portion of that fluid rate with other production. Some portion of this freed-up facility capacity may be used, based on facility constraints and your ability to recognize, and use it.

This will be done either through 1) an active effort to maximize facility throughput by adding wells that are currently shut in, or 2) by passive replacement, which is the result of the increasing drawdown on wells tied into the same system, due to a minor change in overall system pressure.

To estimate this impact, a new term was devised, called the field’s “facility utilization factor (Fuf).” The units of this term are expressed as a fraction and must be estimated based on the overall facility optimization capability. Again, the Fuf is that fraction or portion of the total fluid rate that was removed from the system that you expect to replace.

The next term to define is the average water/oil ratio (WOR) or gas/oil ratio (GOR) of the replacing fluid (RWOR or RGOR). When the field replaces X volume of the fluid that was removed from the system, what you are trying to define is the average WOR or GOR for that new fluid brought into the system. In some fields, you might assume that this value is the average field WOR or GOR. In general, this would be true if all of the replacement fluid is passive. This is the most optimistic value you should use. A more conservative value to use is the marginal WOR or GOR, which can be defined as the threshold ratio at which you chose to shut in wells rather than produce them. This is only true where all fluid replacement comes from bringing on shut-in wells. This shut-in threshold is a more accurate value. The expected value for the replacing fluid will be somewhere between these two terms, as used in the example. In general, if you are actively replacing the fluid, then Fuf should be high (>50%); in this case the WOR or GOR should be closer to the marginal value. If most of your fluid is passively replaced, then Fuf should be low (<30%) and the WOR or GOR should be closer to the field average.

The next term is the Qfr (total fluid rate remove) This can be simply defined as the total fluid rate before treatment minus the total fluid rate after treatment.

For Water Shutoff (WSO)

Qfr = (Qwi − Qwa) or (water rate before treatment − water rate after treatment). Units are in BWPD, and only for the well or pattern treated.

For Gas Shutoff (GSO)

Qfr = (Qgi − Qga) or (gas rate before treatment − gas rate after treatment). Units are in Mcf, and only for the well or pattern treated.

Now that all the necessary elements are defined, the following equations generate the indirect oil rate benefit, Qoid.

For WSO: Qoid = ((Qfr × Fuf) + (Qod)) / (1 + RWOR)

For GSO (or CO2): Qoid = ((Qfr × Fuf) / (1+ RGOR)

The resulting units are in BOPD.

Operating Expense Savings: Qoes

The third beneficial element is the operating expense savings. The operating expense savings is generated by not having to handle and reinject the water or gas that is not replaced by the system. To simplify this element, a manipulation of the value is done to generate an “equivalent net oil benefit (E-NOB).”

“Equivalent” denotes conversion of the operating expense cost-savings element into an equivalent of oil production benefit. Qoes is derived from the operating expense savings that is generated from not handling the “net fluid removed (Qnfr).”

This term is shown by the following equation:

Qnfr = Qfr × (1 − Fuf)

For WSOs, this results in BWPD units; for GSOs, the result is in Mcf/D.

The real key is to properly define the cost of handling the undesired fluid, which we define by the term Puf. The units of this term should be in $/bbl for water or $/Mcf for gas/CO2. This term requires some extensive background and knowledge of your field operating expenses and may not be readily available. Even if no accurate value can be generated, you should be able to generate a conservative estimate. That value can then be used to further your understanding of the total solution benefit generated by the treatment. Please remember, when you estimate or generate this value, be conservative; only generate the cost that is directly variable and truly depends on handling of that fluid volume. For example, the cost of generating the horsepower to lift a barrel of water, plus the cost of treating that water with corrosion inhibitors and/or de-emulsifiers, and finally the cost to reinject a barrel of water to replace the voidage.

All these terms are the true incremental costs associated with handling each barrel of water. Be conservative, do not include all the fixed costs that are associated with maintaining the overall system or that cannot be eliminated just because a small volume of the whole is removed from the process.

Finally, to make these units equivalent to the other terms, divide this dollar-cost savings benefit by the revenue generated from the production of a bbl of oil. We define this term as the N$PBO (net $ per bbl of oil) and express it as:

N$PBO = (sales price for bbl of oil − severance tax – royalties − tariffs)

Some might argue that you should also subtract items like working interest, or operating expenses. But remember, this method equates the cost savings generated by eliminating the cost of handling undesired fluid; this savings will come directly out of the net revenue excluding only severance taxes, royalties, and tariffs.

Thus, Qoes is defined as:

Qoes = (Qnfr × Puf)/N$PBO

This technique is used to generate a combined net benefit on like terms. By doing this, it gives us a relative understanding of the impact of Opex savings, while maintaining the real dollar value of the overall program. In addition, this method allows incorporation of an automatic reduction in the benefit over time through use of a decline rate on this factor.

Total Solution Benefit: Qsb

To generate the estimated total solution benefit (SB) we simply combine the three elements of direct rate benefit (Qod), indirect rate benefit (Qoid), and Opex savings in an equivalent oil rate (Qoes).

Qsb (E-NOB in BOPD) = Qod (BOPD) + Qoid (BOPD) + Qoes (EBOPD)

Solution Benefit Example

Table 1 is an example of how the initial solution benefit can be calculated. This case is a WSO treatment, and the values are made up, but are typical for many fields.

Qod = (250 BOPD – 200 BOPD) = 50 BOPD

Qfr = (6,000 BWPD – 1,000 BWPD = 5,000 BWPD

Qoid = ((5,000 BWPD × 0.1) – (50)) / (1+30) = 16.0 BOPD

Qoes = [(5,000 BWPD × (1-0.1)] × (0.20 $/bw) / (39.42 $/bo) = 22.7 EBOPD

Thus, a better estimate of the true E-NOB of executing this treatment is

Qsb (E-NOB) = (50 BOPD + 25.5 BOPD + 36.2 EBOPD) = 88.6 EBOPD

Table 1—Example WSO values for a typical conformance problem.
Table 1—Example WSO values for a typical conformance problem.

Projecting Total Rate Stream or Volume Benefit

To project the full life benefit of the solution, we need some way to estimate the benefit decline. If enough data exists for past performance of similar solutions, that data can be used to estimate the decline. However, often that data will not exist, and the benefit decline rate must be estimated.

In addition, the Qod will generally decline, at a different rate than the Qoid and the Qoes. To estimate the overall decline rate from the cumulative benefit without field data is difficult. Based on normal production well or pattern performance trends, an estimate for the decline rate for the Qod can be assumed. However, as the undesired fluid returns the observed decline rate on the Qoid and Qoes is often greater.

Unless you have made a careful comparison of past solutions, it is almost impossible to get an accurate estimate of these decline rates. For that reason, a conservative estimate of this decline rate should be used. A reasonable recommendation is to double the field decline rate. We can then calculate the cumulative additional E-NOB generated by the solution until it returns to the original well rate or, we can truncate the benefit at some estimate point in time like 10 years.

Based on a normal well decline rate of 10% per year and an additional decline rate for the SB of 10% per year, an expected cumulative E-NOB would be approximately 140 MBO (Fig. 2).

An example of the estimated overall value generated.
Fig. 2—An example of the estimated overall value generated.

Remember, this is an equivalent volume and cannot be taken as reserves, and the best way to estimate these values is to establish actual field data trends. Without field data, it is important to run sensitivities. This is easily done by entering the formulas into a spreadsheet and changing the additional decline rates to match what you see in the field. Using these techniques, you will be able to estimate the cumulative benefits of future work with much greater confidence in their overall benefit.

Application of Economics

Up to this point, we have only discussed the elements to estimate the equivalent rate benefits generated from conformance solutions. To show the value that is generated, we need to incorporate the cost of doing the problem diagnostics, and the work completed to generate and execute the solution, etc. Using these costs, the Qsb flow stream in E-NOB and the N$PBO defined earlier, we can generate an incremental cash flow stream that will provide additional insight into the potential value that can be created.

The final elements needed are the desired discount rate and a price forecast for oil. For the case shown in Fig. 2, the following parameters were used:

Cost to diagnose, generate, and execute solution = $1 million

Discount rate = 10%

N$PBO = $39.45–assumed constant oil price over time.

Using these values and the rate stream generated from the example, the estimated overall value generated is

NPV10 = ~ $3.1 million with an estimated payout = approximately 10.5 months.

Overview

Although this analysis is still rather conservative, it provides a simple methodology that can be adjusted and tested for sensitivity. In this way, a more complete view or understanding of expected results and key factors can be generated. This analysis was built for initial screening criteria or a simple review of the expected rate benefit and resulting financial performance. This analysis does not incorporate all tax implications.

The key point to remember is that conformance work often results in significant indirect rate and operating expense benefits that should be included when comparing the value of this work to other opportunities. In many companies this is not done, and thus work to improve sweep efficiency or solve conformance problems goes undone because the work is not properly valued.

For Further Reading

SPE 103044 The Successful Evolution of Anton Irish Conformance Efforts by D.D. Smith, M.J. Giraud, and C.C. Kemp, Occidental Petroleum, et al.

SPE 190209 Identification, Problem Characterization, Solution Design and Execution for a Waterflood Conformance Problem in the Ekofisk Field–Norway by G. Aamodt, ConocoPhillips Skandinavia AS; S. Abbas, ConocoPhillips Co.; and D.V. Arghir, ConocoPhillips Skandinavia AS, et al.

David Smith, SPE, is currently the president and principal advisor for Oilfield Conformance Consulting LLC and an adjunct professor for Missouri University of Science and Technology (MS&T). Prior to his current efforts and for approximately 20 years, Smith was the global conformance engineering advisor for either ConocoPhillips or Occidental Petroleum. Prior to that he was a project manager in conformance water management for Halliburton and held several positions within ARCO that were associated with profile modification and sweep improvement. Smith has been an active SPE member for more than 45 years. He was the technical program chairman for the 2014 SPE EOR/IOR Conference in Tulsa, a past co-chairman of the SPE EOR/IOR TIG (Technical Interest Group), and an SPE Distinguished Lecturer in 2019–2020. Smith holds a bachelor’s degree in geology from Pacific Lutheran University and an MS in petroleum engineering from Stanford University.