An Interactive 5-Day Training Course
Volumetrics & Prospect Risking Using MS Excel
Volumetrics and Risking in Excel
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Duration
5 Days
Price
$ 2,000
Starting From
02 Aug 2027
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Volumetrics & Prospect Risking Using MS Excel
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Volumetrics & Prospect Risking Using MS Excel - GG-VOL-EXCEL-PEA27
| Code | Date | Time | Duration | Location | Currency | Early Bird Fee Per Person |
|---|---|---|---|---|---|---|
| GG-VOL-EXCEL-PEA27 | 02 - 06 Aug 2027 | 10 AM CST | 4 Hours Per Day |
Online |
USD |
2000 |
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Volumetrics & Prospect Risking Using MS Excel
This training covers volumetric estimation and prospect risking built in MS Excel. It works through the volumetric equation and its inputs, distribution construction, Monte Carlo simulation without add-ins, dependency and correlation, gross rock volume uncertainty, chance of success assessment, expected value and portfolio aggregation, sensitivity analysis and the presentation of probabilistic results.
Description
Probabilistic volumetrics is performed in most organisations using commercial add-ins that take distributions as inputs and return a result. Building the same calculation in a spreadsheet, using only standard functions, makes every step visible: how the distributions are sampled, how the correlations are imposed, how the aggregation works and which input is driving the width of the answer. It also removes the dependence on a licence and makes the calculation auditable by anyone.
This training builds the whole workflow. The volumetric equation and its inputs are established first, covering each term and its derivation. Distribution construction follows, covering the derivation of input ranges from data, from analogue and from judgement, and the selection of distribution shapes. Monte Carlo simulation without add-ins is then developed in detail, covering the sampling of each distribution type from standard functions and the construction of a simulation that runs in a spreadsheet. Dependency and correlation follow, covering the imposition of rank correlation between inputs. Gross rock volume uncertainty is then addressed. Chance of success assessment follows. Expected value and portfolio aggregation are then developed. Sensitivity analysis follows. The training closes with presentation.
Monte Carlo simulation requires only the inverse distribution functions and those are standard. Sampling a lognormal distribution is the inverse lognormal function applied to a uniform random number; the same approach samples normal, triangular, uniform and beta distributions. A table of rows, each row drawing a sample for every input and computing the resulting volume, is a complete Monte Carlo simulation, and a few thousand rows are enough for stable percentiles. The whole mechanism is a dozen formulas and understanding it changes how the results are read.
Correlation between inputs is routinely ignored and changes the answer. Porosity and net to gross are usually positively correlated because both reflect reservoir quality; area and thickness are correlated through the structural geometry. Sampling them independently generates combinations that do not occur, which widens the distribution and distorts its shape. Imposing rank correlation in a spreadsheet is a short exercise, and the comparison between correlated and independent results makes the effect obvious.
Gross rock volume usually dominates the uncertainty in an undrilled prospect. Area, thickness and the geometry relating them carry the structural and depth conversion uncertainty, and their combined contribution typically exceeds that of the reservoir and fluid parameters. The practical consequence is that effort spent refining porosity estimates is often misdirected while the depth conversion uncertainty remains unexamined. A sensitivity analysis on the completed simulation shows this directly and redirects the work.
Finally, the chance of success and the volume distribution must be kept separate. The volume distribution describes how large the accumulation would be if it exists; the chance of success is the probability that it exists at all, assessed from the independent probabilities of source, reservoir, trap, seal and timing. Multiplying them gives the expected value, which is the number for portfolio comparison. Confusing the two, or embedding a risk factor inside the volume distribution, produces numbers that cannot be aggregated or compared.
By the end of this training, participants will be able to:
- Build the volumetric equation with explicit inputs
- Derive input distributions from data, analogue and judgement
- Select appropriate distribution shapes and parameters
- Construct Monte Carlo simulations using standard spreadsheet functions
- Impose rank correlation between dependent inputs
- Model gross rock volume uncertainty including depth conversion
- Assess chance of success from independent play elements
- Calculate expected value and aggregate across prospects
- Perform sensitivity analysis and identify the dominant inputs
- Present probabilistic results clearly to decision makers
The training is spreadsheet building throughout on real prospect data. Participants construct complete Monte Carlo volumetric models from first principles, compare correlated against independent results, and run sensitivity analyses. Results are compared against commercial add-in output for the same inputs. Participants present their probabilistic results to the group as a prospect recommendation.
Organisations sending participants to this training will:
- Build probabilistic volumetrics that can be audited
- Impose correlation between dependent inputs
- Identify the inputs that actually drive volume uncertainty
- Keep chance of success separate from volume distributions
- Aggregate prospects correctly for portfolio comparison
- Reduce dependence on add-in licences for routine work
Participants will:
- Build Monte Carlo simulations from first principles
- Derive and justify input distributions
- Handle correlation correctly
- Assess chance of success
- Run and interpret sensitivity analysis
- Present probabilistic results credibly
- Exploration geoscientists assessing prospects
- Geoscientists performing volumetric estimation
- Reservoir engineers producing in-place estimates
- Planning and portfolio staff
- Commercial staff using volume ranges
- Technical staff reviewing volumetric work
- Graduate geoscientists in exploration teams
Module 1 - The Volumetric Equation
- Equation forms for oil and gas
- Gross rock volume term
- Net to gross term
- Porosity term
- Hydrocarbon saturation term
- Formation volume factor
- Gas expansion factor
- Recovery factor
- Unit systems and conversion factors
- Common unit errors
- Deterministic calculation construction
- Input documentation requirements
Module 2 - Distribution Construction
- Deriving ranges from well data
- Deriving ranges from analogue fields
- Expert judgement elicitation
- Distribution shapes and their selection
- Normal and lognormal distributions
- Triangular and uniform distributions
- Beta and truncated distributions
- Parameter specification from percentiles
- Minimum and maximum bounds
- Testing ranges by stating extremes
- Documenting distribution bases
- Reviewing distributions critically
Module 3 - Monte Carlo Without Add-Ins
- Random number generation
- Inverse transform sampling
- Sampling a normal distribution
- Sampling a lognormal distribution
- Sampling a triangular distribution
- Sampling uniform and beta distributions
- Simulation table construction
- Number of trials required
- Convergence checking
- Percentile calculation from results
- Histogram and cumulative plotting
- Recalculation control and seeds
Module 4 - Dependency and Correlation
- Independence as a default assumption
- Physical basis for correlations
- Porosity and net to gross correlation
- Area and thickness relationships
- Saturation and porosity correlation
- Rank correlation concept
- Imposing rank correlation in a spreadsheet
- Correlation matrix specification
- Effect of correlation on the result
- Over-correlation and its effects
- Testing correlation assumptions
- Documenting dependencies
Module 5 - Gross Rock Volume Uncertainty
- Gross rock volume components
- Area and its uncertainty
- Depth conversion uncertainty
- Structural interpretation uncertainty
- Area depth relationships
- Volume from area depth curves
- Geometric factor approaches
- Contact depth uncertainty
- Spill point and closure failure
- Probability of a valid trap
- Combining structural and contact uncertainty
- Dominance of gross rock volume uncertainty
Module 6 - Chance of Success
- Play element definitions
- Source and charge probability
- Reservoir presence and quality probability
- Trap probability
- Seal probability
- Timing and preservation probability
- Independence of elements
- Combining probabilities
- Shared play risk against prospect risk
- Calibration against drilling outcomes
- Common risking errors
- Documenting the risk assessment
Module 7 - Expected Value and Aggregation
- Expected value calculation
- Risked against unrisked volumes
- Mean against median reporting
- Portfolio aggregation methods
- Arithmetic aggregation and its error
- Probabilistic aggregation
- Dependence between prospects
- Common risk and its aggregation effect
- Segment aggregation within a field
- Multi-prospect campaign value
- Expected monetary value in outline
- Ranking prospects for drilling
Module 8 - Sensitivity and Presentation
- Sensitivity analysis methods
- Correlation based sensitivity
- Tornado plot construction
- Spider and contribution plots
- Identifying dominant inputs
- Redirecting effort from sensitivity results
- Value of information considerations
- Presenting cumulative distributions
- P90, P50 and P10 reporting conventions
- Communicating ranges to decision makers
- Avoiding false precision
- Documenting the assessment
Upon successful completion of this training course, delegates will be awarded an official Certificate of Completion issued by the Petroleum Engineers Association (PEA), an ISO 9001:2015 certified training organization. The certificate carries 10 Credits and formally records the total learning hours completed.
Each certificate is signed by the Course Facilitator and the CEO of the Petroleum Engineers Association, and serves as verifiable proof of professional training that delegates can present to employers and professional bodies worldwide.
Frequently Asked Questions
All course bookings made through PEA are strictly non-refundable. By registering for a course, you acknowledge and accept that all fees are payable in full and are not subject to refund under any circumstances, including changes in personal or professional commitments or partial attendance.
PEA reserves the right to make reasonable adjustments to course content, trainers, or schedules where necessary, without entitling delegates to a refund. Comprehensive details of each course — including objectives, target audience, and content — are clearly outlined before enrolment, and it is the responsibility of the delegate to ensure the course's suitability prior to booking.
For any inquiries related to cancellations or bookings, please contact our support team, who will be happy to assist you.
