spe-109555-pa

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1/8610 August 2009 SPE Reservoir Evaluation & Engineering

Reservoir Technical Limits: A Framework forMaximizing Recovery From Oil Fields

P. Craig Smalley, Bill Ross, Chris E. Brown, Tim P. Moulds, and Mike J. Smith,SPE, BP

Copyright 2009 Society of Petroleum Engineers

This paper (SPE 109555) was accepted for presentation at the 2007 SPE AnnualTechnical Conference and Exhibition, Anaheim, California, 1114 November, and revised

for publication. Original manuscript received for review 23 July 2007. Revised manuscriptreceived for review 4 March 2009. Paper peer approved 7 March 2009.

Summary

The Reservoir Technical Limits (RTLTM) approach described hereinhas proved highly effective at identifying those activities and tech-nologies required to push oilfield recovery factors toward theirmaximum potential. It combines classical reservoir engineeringapproaches, together with knowledge of existing and novel recovery-enhancing technologies, to create a common framework for identify-ing specific actions to increase recovery factor. RTL is implementedin a structured workshop supported by a software toolkit.

The RTL workshop involves the cross-disciplinary field team(in-depth field knowledge), external technical experts (challenge,cross-fertilization), and trained facilitation. The software toolkitencourages innovation in a structured and reproducible mannerand documents the outcomes in a consistent format. The RTLconceptual framework represents a recovery factor as the product

of four efficiency factors: (1) pore-scale displacement (microscopicefficiency of the recovery process); (2) drainage (connectedness toa producer); (3) sweep (movement of oil to producers within thedrained volume); and (4) cut-offs (losses related to end of fieldlife/access). RTL encourages identification of new opportuni-ties, specific activities or projects that, if implemented, increaseone or more efficiency factor, and thus increase recovery relativeto the current field Depletion Plan. New ideas are stimulated bycomparing current efficiency values with the effects of successfulprescreened activities from analogue fields. The identified oppor-tunities are validated by benchmarking: (a) internally, comparingrecovery factors derived from summing the opportunity volumeswith recovery factors derived from the expected efficiency factorincrements; and (b) externally, comparing with analogue fields.

The result is a prioritized list of validated opportunities and an

understanding of how each activity affects the reservoir to increaserecovery. The opportunities (and any required new technologies)are valued in terms of the resultant incremental barrels. The RTLapproach is a significant innovation, because it provides a system-atic frameworkto: (a) identify new recovery-increasing activitiesacross a portfolio of fields; (b) engender ownership of these activi-ties by the individual field teams; and (c) identify the technologyrequirements to progress the opportunities. Now, having beenimplemented in more than 200 fields, this systematic approach hasenabled opportunity descriptions/values and technology require-ments to be compared consistently across all fields, therebyimproving project prioritization and focusing corporate technologydevelopment and deployment onto the highest impact areas.

IntroductionWhen oil companies are given stewardship of valuable subsurfaceoil resources, maximizing recovery of that resource is an importantaspect of responsible asset management. Being able to maximizeeconomic recovery from an incumbent resource position is advan-tageous both for the company and host nation alike.

But, what is that maximum-recovery potential and how canit be attained? Why do recovery factors for the vast majority ofoil fields still languish lower than 40%, despite the availability ofdrilling and enhanced oil recovery (EOR) technologies that haveenabled some fields to reach more than 70%?

In 2002, we conducted a root-cause analysis of published and

internal company data to determine the critical success factors forincreasing recovery factor. Some issues were obvious, such as theneed to reduce the cost of available technologies. Other factorswere more surprising.

At the individual field level, key success factors are that the fieldteam needs to have a systematic way of understanding their fieldperformance, and a systematic way of assessing what technologiesare suitable for increasing recovery in their specific circumstances.Activities to increase recovery need to be packaged as projects ratherthan vague technology applications, and these projects need to beowned and promoted by the field team, not by a remote technologygroup. Further, the field team needs a clear and consistent way ofcommunicating the nature and value of the projects to compete forinternal company funds. They also need a consistent way of articulat-

ing their need for new technologies, and the value they would extractfrom such technologies by deploying them in their field.At the corporate level, firms need a consistent view of their

full potential portfolio of recovery-increasing projects to be able tomake decisions about which ones to fund. They need to understandwhich existing technology capabilities are advantaged in each fieldto determine where to target technology deployment. Particularlyimportant for long-term growth is a systematic way of gauging theneed for new technologies, and the value added by each, so thatstrategic decisions can be made about research and development(R&D) funding.

Stemming from this review, a new systematic approach toopportunity identification and description was developed at BPcalled Reservoir Technical Limits (RTLTMRTL is a registeredtrade mark of BP plc). This approach, which has been applied to

more than 200 oil and gas fields during the last 5 years, has provedhighly effective in determining the practical recovery potential ofan oil or gas field, as well as identifying and prioritizing specificactivities that help increase recovery toward that ultimate target.This paper outlines the approach as applied to oil fields, alsoproviding some examples of the benefits. A subsequent paper willoutline the application of the RTL approach to gas fields.

The Reservoir Technical Limits Concept

RTL determines the life-of-field recovery potential of an oilfieldand the steps needed to get thereby combining the fol-lowing key ingredients:

Depth of technical knowledge of the individual oil field,together with breadth of experience of other fields and whatworked for them

Innovation, creativity, and awareness of the latest technolo-gies, together with rigorous quality-control to exclude unrealisticor purely fanciful ideas

Field specificity, so the identified opportunities really suit thefield in question, but combined with a consistent approach anddocumentation/reporting mechanism, so that every opportunity inevery field in a company portfolio can be compared and prioritizedon a level playing field.

To incorporate these varied ingredients, RTL consists of thefollowing components: (1) a structured workshop owned by thefield team but embracing external perspectives; (2) a conceptualframework that probes the performance of each field in a consis-tent manner and prompts new ideas in a structured way; and (3)supporting software tools that help with screening, quality control,

benchmarking, and consistent documentation. RTL is applied toan oil field using the following process:

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1.Before the workshop, apply prescreening tools to prepopu-late a list of high-potential field-specific technologies.

2.Engage the right people: the RTL workshop combines the fieldteam, external technical experts, and specially trained facilitation.

3.Use an RTL conceptual framework, in which the recoveryfactor is broken into four component efficiency factors, to achievea good understanding of the Base. This involves consensus onwhat the field has delivered so far and how, and what will havebeen delivered when the activities in the current depletion planhave been implemented.

4.Use the RTL conceptual framework, seeded by examples ofwhat has worked elsewhere and the technologies identified in (1),

to drive the generation of new opportunities. An opportunity isdefined as any activity that can increase the recovery factor com-pared to the current depletion plan.

5.Describe the opportunities and perform a preliminary priori-tization based on doability, cost, and timescale.

6.Quality control the new opportunity set using an internalconsistency check and external benchmarking based on globalanalogue data.

7.The software toolkit facilitates steps 1 through 6, and enablesthe results to be captured, analyzed, and presented in a consistentformat. The opportunity set then passes into the next stage oftechnical workopportunity progression.

The following sections describe how these steps are imple-mented in practice. Subsequent sections deal with examples to

illustrate the benefits.

Application of the RTLTMConcept

Prescreening. Screening criteria have long been used to determinewhether or not a reservoir is suitable for the application of varioustechnologiesfor example, improved oil recovery (IOR) processes(Al-Bahar et al. 2004; Taber et al. 1997a; 1997b). The applicabil-ity of new recovery technologies to a field can be estimated basedon the degree of fit between the reservoir/fluid properties of thefield in question and the critical success factors for each recov-ery-enhancing technology. Some have tried to do this in a purelymathematical manner, using objective functions and optimizationapproaches (Pardo-Torres et al. 2007). However, RTL prescreeningis not intended to come up with either the answer, or to pre-emptdiscussion by overzealously screening out opportunities. Rather,

the idea is to screen-in opportunities by using coarse (relaxed)screening criteria, such that only the most inappropriate technolo-gies are excluded from subsequent discussion.

Screening criteria have been developed based on a combina-tion of published data and new in-house criteria. The criteria wererigorously tested against an extensive in-house reservoir propertydatabase representing many hundreds of reservoirs. The screeningcriteria are applied before an RTL workshop using field data fromthe in-house database. The RTL discussion is thus primed to starton a positive note, with a list of suggestions that may work.

RTL Workshop.This cross-disciplinary workshop is the main vehi-cle for applying the RTL process. In this forum, the field team bringsto the table a deep understanding of their asset, its development storyso far, the reservoir mechanisms and so forth, based on their expe-rience and technical studies. This understanding would have beendeveloped using surveillance, advanced reservoir modeling, andvisualization. The information available and depth of understandingof the field team are criticalany limitations in these constrain thequality of the results. Other attendees are specially selected technicalexperts from outside the field team, who bring experience from otherfields as well as the latest technology perspectives. Both the fieldteam and the external attendees are cross-disciplinary, representingsubsurface, drilling and completions, facilities, commercial, etc.asappropriate for the field in question.

In many cases, bringing the team together with the time andspace to focus on the full life-of-field value of the asset is all thatis needed to precipitate an excellent discussion of future reservesgrowth opportunities. The RTL facilitator is trained to capitalize

on this knowledge and enthusiasm by harnessing it and focusingit to identify a full and thorough opportunity set.

To optimize the quality of technical discussion, a field may besubdivided into different segments/units based on their characterand the recovery processes being used in each; these subvolumesmay be considered separately and subsequently recombined to givea field-wide RTL view. In this way, the RTL approach can handlemultiple-recovery processes deployed independently in differentsubvolumes of a field or simultaneously in the same subvolumes.

RTL Efficiency Factor Framework.The RTL conceptual frame-work represents an oil-recovery factor as the product of fourefficiency factors (Fig. 1). Each efficiency factor is a numberbetween zero and one; when multiplied together, the productEps*Ed*Es*Ecequals the recovery factor. The purpose of usingthe efficiency factors is to understand the broad controls on fieldrecovery factor and to be able to link these with specific efficiency-improving practices. The efficiency factor framework is an exten-sion of the approach often used in classical reservoir engineering(Dawe 2000). The following efficiency factors have been carefullydesigned to relate to specific types of activities that may becomeopportunities for reserves growth.

Pore-Scale Displacement Efficiency (Eps). This is the micro-scopic efficiency of the recovery process, which is the theoreticalmaximum recovery factor if the recovery process could be appliedperfectly throughout the whole field. It is a function of the recov-ery process and how it interplays with pore-scale mineralogy,geometry, chemistry, and fluid characteristics. Depending on thereservoir characteristics,Epscan vary from 90% in miscible-gas injection projects.

Saturation

Eps

1-Eps

Ed

Fault

1-Ed

1-Eps

Distance

Time

1-Ed

1-Eps

1-Es Es

Cut-off

Ec 1-Ec

initial

Sofinal

So

Fig. 1Illustration of the efficiency factors, Porescale Dis-placement (Eps),Drainage (Ed),Sweep (Es),and Cut-offs (Ec)that are used to understand recovery factor and how it canbe increased. Recovery factor is equal to Eps*Ed*Es*Ec, allexpressed as fractions between 0 and 1.

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Drainage Efficiency (Ed). This refers to connectedness to aproducing well. If a part of the reservoir is pressure connected(through the oil-leg) to a producing well on a production timescale,it would be regarded as drained (Fig. 1). In many mature fields,this efficiency factor is close to 1. Situations in which it may belower may include phased developments or highly compartmental-ized fields.

Sweep Efficiency (Es). This refers to movement of oil toproducers within the drained volume. In this paper, we limiteddiscussion to total volumetric sweep, but in RTL workshops, both

areal and vertical sweep efficiencies are distinguished for greaterclarity. The sweep efficiency is influenced by the injector/producerwell pattern and spacing, injection rate, reservoir aspect ratio, res-ervoir heterogeneity, fractures, position of fluid contacts, mobilityratio, density contrasts between injected, and reservoir fluids, etc.In BP, proprietary simulation codes are available for estimatingand visualizing sweep.

Cut-Offs Efficiency (Ec). This refers to loss of recovery relatedto end of field life/access. In most post-plateau fields, produc-tion gradually tails off, with decreasing oil production matchedby increasing water production and operating cost per oil barrel.Actual production ceases before the theoretical maximum produc-tion volume is reached because of critical economic thresholdsbeing reached. This loss of the production tail is represented by Ec, which is 1 the fraction lost. Herein, we considered only theoverall cut-offs efficiency, though for increased clarity, this may bebroken into subfactors related to the three main mechanisms thatcause field production to cease: (1) energy, in which the reservoir isso depleted the wells are not able to flow effectively; (2) facilities,in which facilities are either stretched beyond their design capabili-ties (e.g., water/oil limits) or reach the end of their safe operatinglifetime and cost/benefit does not support facility renewal; and (3)commercial, in which the end of a license agreement means thatproduction ends prematurelyat least for the company holdingthe expiring license.

Defining the Base.The first step to building a good opportunityset is to define its foundation. The Base consists of previouslyproduced oil, plus oil expected to be produced from previously

committed activities as part of the depletion plan. The understand-ing of the reservoir possessed by the field team is used to estimate

the contributions of each of the efficiency factors (Fig. 1) to theexpected Base recovery factor. The Eps may be estimated fromspecial core analysis data, Ed and Es from surveillance and/orsimulation data, and Ecfrom an understanding of the controls onend of field life and commercial models. In cases in which suchdata are insufficientfor example, fields very early in their lifecycleefficiency factor values can be estimated with the help ofthe RTL software tools (Fig. 2), in which efficiency factors canbe estimated based on typical values for standard reservoir andrecovery process types, combined with field analogue data.

The Base efficiency factors for oil fields vary greatly. In gen-eral,Edand Ecare high in mature fields (unless Ecis artificiallyreduced by issues related to commercial terms, such as licenseexpiry).EpsandEsare often where the greatest remaining prizeslay (Fig. 3).

Identification of New Opportunities.The starting point for newideas is the efficiency factors identified for the Base. Opportunitycreation involves a structured but creative conversation about thevarious activities that may be employed to push each efficiencyfactor in turn toward their maximum. Various structured brain-storming techniques may be employed by the trained facilitator,as appropriate for the field in question. Potential opportunities thatmay be discussed include those having passed the prescreeningprocess described earlier, plus other activities typically used toimprove the efficiency factors. Some examples are as follows:

Eps: Waterflooding, enhanced waterflooding (including BPsLoSalTM waterflooding processWebb et al. 2004; Jerauld et al.2006), immiscible gas injection, miscible gas injection, blowdown,microbial EOR, wettability modifiers, and viscosity modifiers, etc.

Ed: Infill drilling, recompletions, sidetracks, and extended-reach wells, etc.

Es: Offtake management; infill wells, sidetracks, fracs; water/gas shut off, Bright Water (Frampton et al. 2004; Yaez et al. 2007),wellwork, and intelligent completions, etc.

Ec: Artificial lift, facilities upgrades, renegotiation of commer-cial framework, capture of nearby production, infrastructure-ledexploration, and gas storage, etc.

Opportunity Description and Prioritization.Each of the identi-fied opportunities are described in a consistent way, including

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 EfficiencyFactor

75%

RF =

30.4%

0.72

0.88

0.50

0.95

DepletionNo P support Strong P support

Waterflood ytilauqhgiHytilauqwoL

EORWater-based Miscible gas

Field 10

Field 11Field 4

Well spacingWide Close

CompartmentsMany None

Heterogeneity/LayeringHigh Low

Dip/GeometryShallow/BW Steep/edge

Field 19 Field 21 Field 22 Field 25Field 23Field 24

Field 20

MobilityLow High

PSAShort Life of field

EnergyLow High

FacilitiesComplex Easy

Field 1Field 3Field 2 Field 7

Field 6Field 8

Field 9Field 5

Field 17Field 18Field 16Field 15Field 14Field 13Field 12

Field 27Field 26 Field 28 Field 30Field 31Field 29

Drainage

Pore Scale Displacement

Sweep

Cut-offs

OIL

FIELD

Efficiency

Factor

Guide

Phased developments

Fig. 2Screen shot from part of the RTL toolkit that aids efficiency factor estimation. Typical ranges are shown for various sce-narios. Values for analogue fields are incorporated for guidance (field names omitted). The efficiency factors are set using thesliders. The resultant recovery factor is recalculated in real time and used to reality-check the efficiency factor values.

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opportunity name, activity involved, expected resource volumeadded by the activity, time-scale, which efficiency factor is beingimproved, likely cost per incremental barrel, probability of success,key risks, technical challenges/barriers, possible technical solu-tions, and an action plan. Based on these descriptors, the opportuni-ties were assigned to one of the following groupings:

Options. Opportunities that are well defined, economic, and

can be implemented in the short term (~1 year). Note: This doesnot mean the opportunity will actually be implemented on thattime-scale; it simply means it may be implemented within ~1year, if selected for progression based on subsequent technical andcommercial analysis.

Possibilities. Opportunities that can be implemented economi-cally using either existing technology or technology that requiresonly incremental development. Possibilities are subdivided intomedium-term(1 to 5 years) and long-term(>5 years).

Barrier Opportunities. The opportunities are so called, becausethere is a barrier to progressing such opportunities (i.e., thesecannot progress without a step change in technology, cost, orcommercial framework, such as license extension to overcome atechnical/commercial barrier). This does not necessarily imply alengthy timescale; some barriers can be overcome quickly withfocused attention.

The opportunities within each of these categories are given apreliminary prioritization based on a variety of factors, such asvolume, doability, and probability of success. For each opportunity,the key risks to delivery are identified, and any risk managementactivities highlighted. Some of the longer-term or more difficult

opportunities may have long lead times or a limited window ofopportunity, and may need urgent action to eventually generatenew reserves; such issues are captured and documented.

Quality Control. The opportunities are quality controlledinother words, checked to ensure that they are internally consistentand reasonable compared to other fieldsin two ways: using aninternal (i.e., within-field) efficiency factor check and comparisonwith external (i.e., vs. other fields) analogue data.

Internal Consistency Check. A simple check for internal con-sistency can be done using the efficiency factor framework, whichinvolves estimating the recovery factor in two independent waysand checking that the results are similar, as follows:

(1)Each of the identified opportunities, whether or not they are

classed as Options, Possibilities, or Barrier Opportunities, have anincremental volume attributed to them, as described earlier. Thesevolumes can be summed together with the oil volume alreadyproduced, divided by the oil in place, and converted into recoveryfactors. This generates three recovery factors, relating to that wouldbe achieved if all of the: (a) Options, (b) Possibilities, and thenfinally (c) Barrier Opportunities were implemented.

(2)The identified opportunities are each aimed at improvingone or more of the efficiency factors. For each opportunity, anestimate is made of how much the relevant efficiency factor(s) areincreased by implementation of that opportunity. This estimationis guided by expert input from RTL workshop participants withexperience of the application of similar opportunities in otherfields. Examining in turn the Options, Possibilities, and Bar-

rier Opportunities, it is then possible to estimate what the newimproved efficiency factor values are, if all the opportunities ineach category were implemented. The revised efficiency factorscan then be multiplied out to give modified estimates of the recov-ery factor after implementation of the Options, Possibilities, andBarrier Opportunities (Fig. 3). Analysis of the efficiency factorsis aided by a software tool, whereby the efficiency factor inputsare dynamically linked to graphics that display the impact of theefficiency factor estimates on recovery factor (Fig. 4).

0.0 0.2 0.4 0.6 0.8 1.0

Eps

Ed

Es

Ec

RF

Base

Options

Possibilities

Barrier

Remaining

Fig. 3Example of efficiency factor values for a mature water-flooded oil field. The Base values represent an understanding

of the reservoir at the time of the RTL review, and include oilpreviously produced plus oil expected to be produced fromalready committed activities. The Options, Possibilities, andBarrier values relate to the efficiency factors expected to re-sult from each activity set identified via the RTL process. Therecovery factor (RF) is the product of the relevant efficiencyfactors (i.e., RF = Eps*Ed*Es*Ec).

S O P B

0.0

0.2

0.4

0.6

0.8

1.0

RF

Fig. 4Screen shots of the tool used to perform an internal consistency check of the opportunity volumes. The left panel illus-trates how the estimated efficiency factors are input for the Base (S = Sanctioned), Options (O), Possibilities (P), and Barrier (B)opportunities. This panel is linked to the diagram on the right, therefore changing the efficiency factors changes the recoveryfactor accordingly (shown by column height; this is method 2 described in the text). The small horizontal lines on the right chartrepresent the recovery factors calculated by adding up the opportunity volumes (method 1, described in the text). If the columns

and horizontal lines match, this indicates the opportunity volumes are consistent with the understanding of the field representedby the efficiency factor estimates.

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The estimates of the recovery factor derived by the two previ-ously discussed pathways are compared graphically (Fig. 4). Ifsimilar, this comparison indicates that, within the uncertainty limits,there is consistency between the description of the opportunity setvolumes (method 1) and the understanding of their impact on thereservoir efficiency factors (method 2), thereby giving confidencethat the opportunity set is reasonable. Minor differences (as in Fig.4) are likely to be within the noise of this semiquantitative approach.However, sometimes, large discrepancies have been identified atthis stage, which may indicate problems, such as opportunities thatduplicate each other (i.e., producing the same barrels in two differ-ent, mutually exclusive ways), misunderstanding the effect of an

activity on an efficiency factor, or even an unresolved problem withdefining the oil-in-place. Whenever such a discrepancy is identified,this leads to an iteration of the process (e.g., deleting or mergingcompeting opportunities) until agreement is reached and a fullyconsistent opportunity set is achieved.

External Consistency Check. BP has an extensive reservoirperformance benchmarking toolkit. This toolkit allows recoveryfactors for the field in question to be compared to those of relevantanalogue fields (i.e., those with similar geology, recovery process,well spacing, and field maturity). A numerical estimation of res-ervoir complexity index (CI) is key to this; the process used hasevolved from the early work of Dromgoole and Speers (1997), nowinvolving more sophisticated scoring and weighting methods. TheCI allows different reservoirs to be compared numerically on the

same graph. The external consistency check simply involves plot-ting the recovery factors for the Options, Possibilities, and BarrierOpportunities derived using the previous method (1), against CI fora range of analogue fields. An example of this is shown in Fig. 5.Herein, for confidentiality reasons, individual analogue field datapoints have been removed and are instead represented by trendlines tuned to the analogue data. In Fig. 5, the recovery factorsderived from the Options, Possibilities, and Barrier Opportunitiesbenchmark well, because they lay very close to the appropriateanalogue trend lines. This indicates the recovery factors are rea-sonable when compared to analogue fields with similar complexi-ties, employing similar recovery processes, and with similar wellspacings. In cases in which significant discrepancies are revealed,particularly when the recovery factors are high relative to the ana-logue data, the opportunity volumes may be adjusted until they are

more in keeping with the analogues.

Data Capture and Follow-Up.The data describing the opportu-nity set plus the relevant background data on the field are capturedin a consistent format with built-in graphics and summary tablesthat illustrate the opportunities and help communicate the resultsto a wider audience. The data resulting from the RTL workshopare uploaded into a global RTL database.

The opportunity set feeds into an opportunity progressionworkflow (Fig. 6), the first part of which is often a more detailed

screening process. The opportunities that make it through this sec-ond, stricter round of screening are prioritized for more detailedtechnical work. The RTL review is only the first step, but it givesfocus and impetus to the critical technical and commercial work thatfollows, to take the opportunities and turn them into a high-qualityportfolio from which projects can be selected for investment.

Case Study 1: New Opportunities in a

Mature Field

This case study deals with a mature onshore oil field with morethan a billion barrels of oil initially in place and more than20 years of production history. The reservoir consists of highlyheterogeneous fluvio-deltaic sands containing 23 API gravityoil. The field was developed initially as a waterflood, with72 oil producers and 33 water injectors, with a well spacing of~80 acres. Subsequently, five gas injectors were drilled, and a

Water-Alternating-Gas process was implemented using a misciblegas injectant (MI). This process was applied to approximately 25%of the field. The result of the effective waterflood, enhanced by gasinjection, and the tight well spacing, was a relatively high Baserecovery factor of ~52%.

The RTL approach was applied to this field in 2006, and theanalysis of the efficiency factors for the Base was Eps = 0.72(this is volume-averaged, derived from pore-scale displacementefficiency factors of 0.53 for the waterflood and 0.90 for the mis-cible gas displacement parts of the field respectively, both derived

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 5 10 15 20 25 30 35 40 45 50

Complexity Index

RecoveryFactor

Barrier

Possibilities

OptionsBase

RF

B

O

P

B

Fig. 5Recovery factors for the Base, Options, Possibilities,and Barrier (circles) compared to analogue-calibrated trendlines of recovery factor vs. complexity index for fields withsimilar Eps (the y-intercept) and well spacings. As more op-portunities are implemented, the Epsincreases because of theEOR, and the well spacing decreases because of infill drilling.In this case, the recovery factors benchmark well.

RTLTMRTLTM

Coarse Pre-Screening

All AvailableTechnologies

PotentialOpportunities

ProgressionProgression

Fine Screening

Opportunities PrioritizedOpportunities

Opportunity Work-Up

Technology Plans

Surveillance Plans

Reservoir Description

Fig. 6The overall workflow in which RTL is implemented. Preliminary coarse prescreening feeds potential opportunities into the

RTL workshop. Opportunities are devised and quality controlled in the RTL. Subsequently, these are fine screened to prioritizethe opportunities for further work. These opportunities feed into a workflow called Opportunity Progression.

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from core-flood data);Ed=0.90 (derived from field-wide pressure

surveillance),Es=0.85 (derived from reservoir simulation sweepanalysis, and Ec= 0.97 (derived by application of an economiccut-off to the simulation-derived production profile). The productof these efficiency factors is 0.531, which matches closely the52% recovery factor.

From this Base, the RTL workshop identified a number ofactivities that may increase the efficiency factors, and thus increaserecovery factor (Fig. 7).

Options. The options identified were: (a) implementation ofBPs LoSalTMlow-salinity waterflooding technology (Webb et al.2004) to improve Epsof the waterflood; (b) water injection intothe gas cap improving the Ec by maintaining pressure and thusmaintaining injectant miscibility; and (c) improve the sweep (Es)of the MI by sidetracking MI injectors into optimal positions.

Possibilities. The possibilities involved expanding the through-put of both LoSalTMand MI by tapping into new supplies of theseinjectants, resulting in an improved sweep (Es) and field lifeextension (Ec).

Barrier Opportunities. A rich vein of barrier opportunitiesincludes: (a) late-life sale of gas from the gas cap associated withfield depressurization; (b) expansion of the MI by using miscibleCO2 gas, enabling the full field volume to be covered with theEOR process; (c) increased water-handling capacity to extend fieldlife to higher water cuts; (d) use of Bright Water (Frampton et al.2004) to improve waterflood sweep deep in the reservoir; and (e)extension of the MI to a new isolated part of the field. All theseBarrier opportunities have technical barriers, but each barrier hasan associated set of proposed activities to overcome the barriers(e.g., R&D, field piloting, etc.).

Several of these opportunities are additional to those originallyin the field depletion plan; if implemented in entirety, these oppor-tunities can raise the recovery factor to almost 70% (Fig. 7). Thecorresponding efficiency factors are then Eps=0.84, Ed=0.99,Es=0.89, and Ec=0.99.

Case Study 2: RTL Helps Identify New

Opportunities to Replace Production

The RTL process is ideally repeated at regular intervals, perhapsevery 1 to 2 years, depending on the field in question. Many fieldshave been through the RTL process twice or more. An examplefrom a mature offshore oil field that has undergone the RTL pro-cess three times during a 3-year period is shown in Fig. 8.Thisoffshore field is a large, mature waterflood with more than 20

years of production. It has 45 producers and 27 injectors, and awell spacing of approximately 160 acres. When RTL was applied

for the first time in 2002, already 46% of the in-place oil had been

produced, and the estimated recovery from the existing Base was54% (Fig. 8). A miscible gas injection WAG process was at thattime being applied to approximately 10% of the in-place volume.The efficiency factors were estimated at: Eps=0.80, Ed=0.92,Es=0.76, and Ec =0.95. In the 2002 RTL, the following oppor-tunities were identified:

Options. An extensive infill drilling program, aimed at improv-ing sweep.

Possibilities. Infill drilling aimed specifically at draining anisolated segment, and an extension of the WAG process to cover~50% of the reservoir, improving the volume-weighted Eps.

Barrier Opportunities. Extending the WAG process to cover~80% of the reservoir, coupled with late-life depressurization torecover the injectant.

If all these opportunities were implemented, the predicted res-ervoir technical limit recovery factor would be ~64%, caused byimproving:Epsfrom 0.80 to 0.88,Edfrom 0.92 to 0.95,Esfrom0.76 to 0.80, and Ecfrom 0.95 to 0.96.

1

3

0.50

0.55

0.60

0.65

0.70

Base Options Possibilities Barrier

Reco

veryFactor

MI in Isolated Segment

Bright Water

Increase Water Handling

EOR: CO2Injection

Gas Sales

Expanded LoSalTM

Additional MI SourceMI Sweep Optimization

Gas Cap Water Injection

LoSalTM

Base

Opportunity set

2

33

2

1

45

4

56 6

7

7

8

8

10

9

10

9

Fig. 7An RTL-derived opportunity set for a mature oil field. MI = miscible hydrocarbon injection.

0.45

0.5

0.55

0.6

0.65

0.7

Produced Base Options Possibilities Barrier

Recov

eryFactor

2002

2003

2005

Fig. 8Results from repeated RTL reviews during a 3-yearperiod for a mature offshore oil field. The Base increases from2002 to 2005, representing delivery of new reserves (increasedBase) caused by progression of 2002 Options and Possibilitiesinto the 2005 Base. However, the Options and Possibilities have

also grown, representing progression of 2002 Barrier opportu-nities to create 2005 Options and Possibilities.

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A repeat RTL a year later showed similar results, with onlyminor changes in estimated volumes. However, a third RTL in 2005revealed an interesting pattern of opportunity identification andprogression during that period (Fig. 8). During the intervening 3years, cumulative production had increased to 49%. Nevertheless,the expected Base recovery has more than kept pace with this,increasing significantly in 2005 from 54 to 58% as a result of thoseinfill drilling Options and Possibilities identified in 2002 beingprogressed through to sanction and implementation. The hopperof Options and Possibilities did not become depleted, though; bothactually rosein 2005, because some of the EOR extension opportu-nities in the Barrier category in 2002 had been worked by the field

team, the technical and commercial barriers overcome, and thoseopportunities promoted to Options and Possibilities. Although >30mmbbl of opportunities were promoted out of the Barrier categorybetween 2003 and 2005, in 2005, the Barrier opportunities actu-ally increased, because the 2005 RTL identified three new Barrieropportunities: (1) drilling of small, undrained peripheral compart-ments identified from new seismic data; (2) application of LoSalTM(Webb et al. 2004) to the waterflooded remnant of the field basedon new technical studies; and (3) enhancement of the MI EORprocess by increasing throughput by accessing a larger amountof MI injectant. If all these opportunities were implemented, thereservoir technical limit recovery factor increased from 64 to 67%(Fig. 8), representing final efficiency factors of Eps=0.90, Ed=0.96, Es=0.81, and Ec=0.97. This example illustrates how the

RTL approach can continue to identify new opportunities to growreserves as new data are acquired and more is understood aboutfield performance, and as technology evolves.

Case Study 3: Focusing R&D Investment

The consistent format of the RTL outputs, imposed by the RTLtoolkit used during the RTL workshop, facilitates the simpleuploading of RTL data for each field into a single corporate data-base. The resulting global dataset is an incredibly powerful toolthat links possible future producible volumes to specific activitiesand to the application of specific technologies. Where technologyadvances are necessary (e.g., to unlock a group of barrier oppor-tunities across several fields, it is possible to value the technol-ogy advancement based on the amount of resource it progressesthrough to production. This helps to focus R&D efforts onto the

technologies that have the greatest global impact.In this example, a corporate R&D program needed to estimate

the potential impact of various EOR technologies in one particulargeographical area, to determine whether or not the optimal balanceof R&D effort had been achieved. The kind of analysis availablereadily from the database is illustrated in Fig. 9.A breakdownof the technologies required in the set of EOR-related Barrieropportunities from the geographic region in question, weightedby the expected resource volume to be added by each technology,

is shown in the figure. This kind of data is invaluable at the regionallevel, for technology planning, for developing regional technologystrategies as well as assessing manpower and training require-ments. Looked at globally, this type of data is key to efficientfocusing of R&D resources onto the technologies which, in thefuture, are likely to produce the largest gain.

Conclusion

In the quest to maximize recovery factors, Reservoir TechnicalLimits is a valuable new tool, providing a way of packaging andimplementing both standard and innovative reservoir engineeringapproaches in a practical, consistent, and reproducible manneracross many fields. The RTL process is designed to reach an opti-mal balance between the two conflicting drivers: (1) the need forinnovation and creativity to generate new ideas; and (2) the needfor focus, discipline, and consistency for the process to be efficientand give reproducible high-quality results. The combination of in-field experience (the field team), global technical expertise, andtrained facilitation has proved highly effective and is supported bya proprietary software toolkit. We found it very useful to decon-struct the recovery factor into the four efficiency factorsPore-Scale Displacement, Drainage, Sweep, and Cut-Offsso thatprescreened field-specific activities/technologies to maximize eachefficiency factor can be seeded into the discussion.

Innovation is good, but way-out ideas disconnected from realityor unsupported by understanding of the reservoir are not good

they distort the picture of what is reasonably possible. The qualitycontrol measures implemented in RTL use a simple but effectivemethod to ensure that unrealistic or duplicate ideas are filtered out.These measures consist of: (a) an internal consistency check thatcompares the recovery factor calculated from adding up the oppor-tunity volumes with that estimated by multiplying out the modifiedefficiency factors; and (b) comparison with global analogue fieldsusing an in-house performance benchmarking toolkit.

The RTL process has been in operation for several years, andan extensive database has built up of successful RTL Reviews.Before-vs.-after comparisons show that in almost all cases, newideas are generated, adding to the potential producible volume.Where RTL reviews have been repeated, the trend continues, eachtime expanding the opportunity set through time as more is knownabout the reservoir and as technology evolves. There has been suf-

ficient time to track some opportunities from their conception inan RTL review, into technology planning, technology development,field piloting, and right through to production.

The global dataset represented by hundreds of RTL reviewsand thousands of individual opportunitieseach of which linksa technology and activity to a resulting resource volumeis anextremely useful tool for planning R&D on a variety of scales,from field and regional technology plans through to corporateR&D prioritization.

OtherMicrobial

Miscible

CO2 Immiscible

Gas

Bright

Water

Depressurization

Repressurization

Gas Cap Water Injection

Enhanced Waterflood

LoSalTM

Fig. 9A breakdown by volume of the potential EOR-related Barrier opportunities for one geographical region (other opportunities

related to drilling, facilities, and commercial, etc. are not included). This breakdown illustrates the type of information derivedfrom the global RTL database; it is valuable for developing local technology plans and global R&D strategies.

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This paper focused on the RTL process, but that is only thestart. Opportunity identification through RTL has to be followedby efficient and effective opportunity progression in which eachopportunity is worked up by the field team and aided by technicalexperts as appropriate. The RTL toolkit is designed to link seam-lessly with the subsequent opportunity progression workflow thatturns the ideas into reality.

Acknowledgments

We thank BP for permission to publish. Cliff Black and Gary Nev-ille can be singled out for thanks for their help in devising the RTLprocess. Numerous other colleaguestoo many to mentionhavecontributed to the conception, development, and implementation ofthe processes described herein. Their work is highly appreciated.

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Craig Smalley is currently a senior advisor in SubsurfaceUncertainty and Risk Management, and coordinates the globalapplication of the RTL approach described in this paper. After5 years as a geologist at the Institute for Energy Technology(Norway), he joined BP at their Sunbury Technology Centre. In 20years with BP he has held a variety of R&D and leadership roles.He has a long-term interest in novel approaches to assessingreservoir quality and compartmentalization risks. He holds a BScdegree in geology and a PhD degree in geochemistry andisotope geology from Nottingham University, UK. He has beenan SPE member since 1992. Bill Rossis a reservoir engineer with along and varied career in BP, having held various internationalroles. Currently based in Houston, he is a senior advisor in classical

reservoir engineering. He helped devise and pioneer theapplication of the RTL approach described in this paper. ChrisBrownis a consultant who recently retired from BP after a longcareer that included many key technical and leadership roles,including Director of Reservoir Management and DistinguishedAdvisor. Tim Mouldsis a reservoir engineering advisor with BP inAberdeen, UK. He has worked on many gas injection projects inAlaska and the UK and Norwegian sectors of the North Sea, alsohas interests in assisted history matching and scale-up. He holdsa BS degree in mathematics from the University of Newcastle-upon-Tyne and an MS degree in applied mathematics fromImperial College.Mike Smithhas held a number of senior reservoirengineering roles over a 30-year career with BP, including roles inAbu Dhabi, Alaska, and Colombia. He is currently VP of ReservoirManagement. His interests include quantifying and formalizingconcepts of What Makes a Good Reservoir Plan. He holds a

BSc degree in mathematics and mathematical methods fromCranfield University, UK.

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