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EP00 - In t roducing the E&P Bus iness She l l Learn ing Cen tre

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4. APPRAISAL PLANNING

The fundamental objective of appraisal drilling is to reduce uncertainty. In order to optimise theexpenditure, appraisal decisions must be based on consistent, objective criteria. Some of these areillustrated in this chapter.

OBJECTIVE OF APPRAISAL

Appraisal activities are designed to reduce the uncertainty associated with discovery volumes of hydrocarbons. The information to be collected is aimed at answering one or more combinations of thefollowing questions:

• How much oil and gas is there?• Where is it?• At what rate and how much in total will it produce?

Appraisal is often trying to narrow the range between the low and high estimates of HCIIP Such appraisal,if successful, will therefore steepen the expectation curve (Chapter 3.3) Figure 4.1 shows the expectationcurve of an oil accumulation before and after appraisal activity, which resulted in reduced uncertainties inthe STOIIP values.

Figure 4.1 shows the result of similar appraisal activity which not only reduced the uncertainty (steeperexpectation curve) but also resulted in a changed (increased) expectation value. Sometimes a large 'upside'

potential STOIIP may feature in the expectation curve due to the presence of untested traps in the field. Inthese cases the appraisal activity may be treated in the same way as exploration.

APPRAISAL ACTIVITY

Most appraisal will be in the form of drilling wells, but the principles can be applied to all forms of datagathering, e.g. detailed 3-D seismic to clarify the structure of a field. The principles can also be applied toeach part of a logging and testing programme for a well to ensure that the information being collected isworth the cost of collecting it.

Some examples of appraisal are:• A well drilled to improve the structural control on the flanks of an accumulation, by reducing theuncertainty in the dips seen on seismic.

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• A well drilled to log a fluid contact, where previous estimates were based on pressure data. An estimatebased on pressure data alone may be off by tens of metres, particularly if no water pressures havebeen measured.

• A 3-D seismic survey to improve the resolution of the structure and fault pattern of a field.• Interference pressure tests to check for communication across a fault or continuity of reservoir.• A production test to establish well potential and reservoir parameters such as permeability.• Wells to establish reservoir properties in the water column.

PRACTICAL METHOD FOR CONSTRUCTING EXPECTATION CURVES

In order to decide if, and how much, appraisal is needed, the uncertainties in the factors which determineHCIIP have to be quantified. A practical way of constructing an expectation curve (explained in Chapter3.3) is presented below.

The first step is to estimate low, medium and high values for each of the "input" variables to the volumetriccalculation (gross rock volume, net/gross ratio, porosity, saturation, etc.). By definition these values haveequal probabilities of 1/3. If a lot of data (many wells) is available statistical analysis can be used.Otherwise there is a greater tendency towards the use of experience and judgement.

Note that the uncertainty reduces with increasing information. It is a common problem that, when only afew wells are available, one tends to underestimate the uncertainty.

The L, M & H values of two of the input variables (e.g. bulk volume & net/gross) are crossmultiplied,resulting in 9 products (= net reservoir volume) with equal probability P(x) of 1/9. Multiplying all 9 valueswith the L, M and H of the next variable (e.g. porosity) will yield 27 values (total pore volume) with equalprobability of 1/27. This is illustrated in Figure 4.2.

Multiplying all the variables of the volumetric calculation will yield a number of values for the STOIIP whichhave an equal probability. A plot of these values (in ascending order) vs their cumulative probabilityP(x>=xi) gives the expectation curve for the HCllP. It is advisable to use a spread sheet for all themultiplications, because of the high number of values involved.



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If a computer (spread sheet) is not available, expectation curves of the product can be constructed after

every cross-multiplication (Figure 4.3). Reading off low, medium and high values for this product, will limitthe number of multiplications in each step to nine. The resulting expectation curve for HCIIP will then be lesssmooth.

By multiplying the HCIIP expectation curve with low, medium and high values for the recovery factor (RF)one can construct an expectation curve for reserves.

To estimate the values for gross rock volume, often "minimum", "medium" and "maximum" contourmaps are drawn. The three resulting volumes represent the two extremes of the expectation curve (100%and 0% probabilities) and the medium case, and can be used to sketch an expectation curve for GRV.The low, medium and high values of GRV can be read from this curve, given that they are derived as

the 85%, 50%, 15% cumulative probabilities respectively.



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WHY APPRAISE?

The fundamental objective of appraisal activity is to reduce uncertainty. Uncertainty carries with it apotential cost or penalty. If we develop a field based on the expectation reserves and subsequently find thatonly the low reserves are present, we will presumably have spent more money in developing the field thanwas actually required. Clearly the magnitude of this overspend or 'penalty' will increase if there is moreuncertainty in the reserves figure. This is illustrated in Figure 4.4.

As Figure 4.4 suggests, the development of a field may also be sub-optimal if the size of the field wasunder-estimated. For example, if it turns out that a field can produce at 4000 m 3/d, but only 2000 m3/dpipeline capacity was installed, the extra 2000 m3/d which cannot be exported would incur a costbecause of the lost opportunity. Greater revenues could have been generated by extra money spent on alarger pipeline.

The risk of sub-optimal expenditure can be calculated if the reserves probability density function and thesub-optimal expenditure curve are known:

Risk = Chance x Effect = Probability x sub-optimal expenditure



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In Figure 4.5a the probability density function for reserves is drawn in the same graph as the sub-optimalexpenditure for the field. The shaded area represents the total risk of sub-optimal expenditure. Figure 4.5bis similar, but now the uncertainty of the reserves has been reduced, by additional appraisal. As a result theprobability density function is more narrow and the resulting risk of sub-optimal expenditure smaller. Thedifference between the risk before and after appraisal represents the value of the information gained

from the appraisal activity. This can be directly compared with the cost of the appraisal programme todetermine whether executing the programme is worthwhile or not.

DECISION MODEL FOR APPRAISAL

• Recognise/list uncertainties.- All of them - try to make an exhaustive list.- Challenge your assumptions - the strength of the challenge will depend on what evidence a particularfeature of the model is based.

• Quantify/describe the uncertainties.- Dont limit ranges of uncertainties to observed values - you probably haven't seen the extremes. This isparticularly important when information is more sparse.

- Look at comparable structures and sedimentary environments to help quantify ranges.- Leave statistics to the end - there is little enough data as it is without hiding things in averages.

• Construct an expectation curve using ranges of the separate variables.- Remember to use "low's" and "high's" rather than minimum and maximum values.

• Rank the uncertainties. Which ones should the appraisal programme target?- How will these uncertainties affect your plans and/or actions?

- Can you proceed without resolving some uncertainties (do they have no impact on your futureactions)?- The shape of the expectation curve may show what to appraise first (i.e. the "upside" or the"downside").



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• What data is required to resolve the uncertainties? How can you get it?- New seismic (2D/3D), reprocessing of old data.- How many wells need to be drilled, where, in which direction, etc?- What do you measure in each well (e.g. logs, coring, well testing, seismic calibration)?

• Test appraisal activity against your objectives.- What is the possible reduction in uncertainties?- Is the information going to steepen the expectation curve? How much?- What else might be "seen"?- What might be different?- What are the costs involved?

• Design an appraisal plan.- Is there a preferred sequence?- Is there any optional activity (that depends on the outcome of other data gathering)?- Time schedule, including time required for approval (partners, government).- Consider the HSE aspects of your appraisal plan.



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