IFRS integrated Energy & Gas portfolios

KNIME Analytics Platform
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hey guys , i need help in using the monte Carlo workflow in reference to the oil rig valuation reserve & cost impairment testing

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You need to provide more detail about the workflow you’re referencing and the data source. Also, what are you trying to do?

3 Likes
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"Hi @rfeigel Know-it-All, thanks for the quick response!

I’m building a portfolio project for Energy & Gas IFRS compliance in Kenya (focusing on upstream oil/gas like Tullow Turkana blocks). The goal is Monte Carlo simulation for reserve valuation & cost impairment testing under IAS 36 / IFRS 6 — specifically simulating oil rig / asset recoverable amount vs carrying value, with probabilistic inputs for:

  • Oil price (Brent crude volatility)

  • Reserve volumes (P90/P50/P10 distributions)

  • Production decline rates

  • Decommissioning costs (IAS 37 provisions)

  • Discount rates / forex (USD debt in KES)

Trigger impairment if simulated Value in Use < Carrying Amount.

Data sources:

  • Historical reserves/production: Tullow Oil annual reports (PDF notes on Kenya blocks) + NOCK Kenya PSC model terms.

  • Oil prices: EIA.gov weekly data or Brent futures (CSV from investing.com).

  • Example inputs: Base reserves 500 MMbbl, carrying KSh 50B, rig cost KSh 10B, etc. (I can share sample CSV).

Workflow so far:

  • Extracted data from PDFs using Python pdfplumber/Camelot (the comprehensive workflow from forum: https://forum.knime.com/t/from-pdf-to-table-excel/79955/77).

  • Basic DCF setup with Math Formula nodes.

  • Trying to add Monte Carlo: Loop with Random Number generators (Normal/Triangular distributions) → 10,000 iterations → Statistic views for impairment probability.

I’m stuck on efficient simulation loop (Recursive Loop or Simulation Loop End?) and visualizing impairment distribution (histogram of recoverable amounts).

If anyone has a similar Monte Carlo workflow (even basic risk analysis), or tips for oil/gas inputs, that would be amazing! Happy to share my current .knwf file.

Thanks!"

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Others may disagree, but I don’t think Knime is a good platform for doing Monte Carlo analysis. I’m a huge supporter of Knime, but not for Monte Carlo analysis. There are dedicated platforms which provide a wide variety of distributions and more robust methods for combining distributions. For a number of years, I did fairly sophisticated analysis of financial risk for commercial solar systems. I used ModelRisk which is an Excel plugin. (Lots of Excel snobs object to doing anything in Excel, but ModelRisk worked well for me.) Modelrisk has a 15 day free trial. There are other platforms out there. I’d recommend looking elsewhere.