Exploration Portfolio Chosen by the Optimizer

The business question

The exploration team has eight drill-ready prospects in three plays and US$270 million for next year's wells. Prospects in a play share its risk: if the play fails, all of them are dry. OG-06 compared four programmes and recommended the balanced one.

Here the ModelRisk Optimizer searches all 256 combinations of wells for the highest expected value that fits the budget with at most a 20% chance of finding nothing.

Who it is for

Exploration managers, portfolio and planning teams, and geoscientists who risk prospects.

Main outputs

The Optimizer's drilling programme against a starting plan (OG-06's Balanced programme, the one it recommends) · for both: the expected value (EMV), the expected cost, the chance of finding nothing, the chance of losing money and the range of programme NPV · the chance of a dry year with and without shared play risk · what drives the value of the Optimizer’s plan.

How the model works

Five sheets after this one, read from left to right. Each one feeds the next.

1. 1

   Inputs sheet

   The exploration budget, the largest acceptable chance that the programme finds nothing, and for each play the chance that it works at all.

2. 2

   Decisions sheet

   Eight yes/no cells, one per prospect: 1 drills it. The Optimizer changes them; beside them is the starting plan, OG-06's Balanced programme. Below are the goal (the highest mean programme NPV) and the limits (the expected cost within the budget, the chance of finding nothing at most the limit).

3. 3

   Prospects sheet

   Each prospect's chance of success if its play works, its well cost (PERT) and its value if it finds oil (Lognormal from P90 and P10). In every iteration one Bernoulli trial per play decides whether the play works and one per prospect the local outcome. A prospect is a discovery only if both succeed.

4. 4

   Programmes sheet

   For both plans: the expected cost, the expected value and the chance of finding nothing, calculated exactly. And for this iteration the discoveries, the programme NPV and whether it finds nothing, on the same simulated outcomes.

5. 5

   Results sheet

   Both plans side by side: EMV, expected cost, the chance of finding nothing and of losing money, the range of NPV. The chance of a dry year with and without shared play risk; what drives the plan's value.

ModelRisk techniques

• ModelRisk Optimizer: eight yes/no decisions
• Budget as a value limit
• Chance of a dry year as a probability limit
• Shared play risk VoseBernoulli
• Both programmes on the same samples

Find similar models

Product

• ModelRisk
• Optimizer

Type

• Simulation
• Optimisation

Application

• Choosing a strategy
• Valuation and investment

Uses

• PERT
• Lognormal
• Bernoulli
• Sensitivity analysis (tornado)

Inputs and assumptions

Every assumption in the model, with its uncertainty and where it comes from. The figures are illustrative.

Units and conventions

Money

US$ million (US$m), present values at the time of the drilling decision.

Value if discovered

NPV of developing a discovery, after development costs and tax, before the cost of the exploration well.

P90 / P10

Petroleum convention for prospect values: P90 is the low estimate (90% chance of being exceeded), P10 the high one.

EMV

Expected monetary value: the average programme NPV over all simulated outcomes, dry holes included.

Drill

1 drills the prospect next year, 0 leaves it for later.

Key assumptions and limitations

Dependence

Prospects in the same play share the play's risk. Once the play works, their local risks are independent. The plays are independent of each other.

Values

A discovery's value does not depend on other discoveries: no shared facilities and no capacity limits.

Budget

As in OG-06, the budget limits the expected cost of the wells drilled (the sum of their mean costs). In a given year the wells may cost more or less.

Optimizer

Each programme the Optimizer tries is judged on the same 10,000 simulated outcomes (common random numbers, seed 1) as the simulation on the Results sheet, so programmes are compared fairly and the limits met in the run hold on the Results sheet too.

Data

Prospects, chances and values are invented for this example.

How to use it

1. Review the plays and set the budget and the acceptable chance of finding nothing on the Inputs sheet. The prospects are on the Prospects sheet.
2. On the ModelRisk ribbon, open the Optimizer: the task is saved in this workbook. Press Start. When it finishes, apply the best solution: the 1s and 0s on the Decisions sheet change.
3. Run a simulation from the ModelRisk ribbon (10,000 samples with a fixed seed are set) to compare the new programme with the starting plan on the Results sheet.
4. To watch the search from the beginning, copy the starting plan onto the Optimizer’s plan first.

The tornado chart fills in after a simulation with ModelRisk’s classic engine.

ModelRisk functions used

ModelRisk Optimizer

Chooses the wells: the highest mean programme NPV, with the expected cost within the budget and the chance of finding nothing at most the limit.

VoseBernoulli

Whether each play works and whether each prospect succeeds locally: one trial per play and one per prospect.

VosePERT, VoseLognormalAlt

Well cost from low, most likely and high. Value if discovered from its P90 and P10. VoseMean of the Lognormal gives the mean value for the exact EMV.

VoseSimMean, VoseSimProbability, VoseSimPercentile

EMV, chances and percentiles of both plans on the Results sheet.

VoseSimSensitivityMean

The tornado chart: the inputs that move the mean NPV of the Optimizer’s plan most.

Further reading

• Sensitivity analysis in Excel: a tornado chart step by step (Vose guide)
• Rose, P. R. (2001). Risk Analysis and Management of Petroleum Exploration Ventures. AAPG Methods in Exploration 12.
• OG-06 Exploration portfolio with shared play risk: the same prospects, with four drilling programmes compared side by side.