K&F’s proprietary enabling technology: Fully Probabilistic Asset (E)valuation Framework

  • Strongly top-down centric (fast results with focus on integration)
  • At the core is a state of the art techno-commercial simulator to model assets
    • Covers all aspects, i.e. scheduling, production, expenditure load and economics
    • Each asset model can comprise any number of phases&contractors
    • Individual assets can be rolled up into groups of assets
    • Full flexibility to define relationship between phases / assets (timing, etc.)
  • High performance computing engine & environment
    • Industry grade functions & optimizers
    • Fully parameterized with full audit trail
    • Dramatic improvement in efficiency compared to spreadsheet based methods (e.g. runs 10,000 full asset models for Monte-Carlo analysis)
    • Utilizes techniques developed for history matching (e.g. risk/uncertainty framework)
  • Sophisticated post-processing capabilities
    • Focus on high end visualization

K&F workflow

The described workflow below enables the full reservoir assessment using propriety software solutions.

Reservoir Fluid System
Develop a system of correlations and analytics to identify reservoir fluid system


  • Extensive library of state of the art correlations that is constantly updated and customized
  • Advantages compared to conventional PVT analysis:
    • Minimum input of known data (such as data room typical)
    • Measured data and offset data where available for calibration & QC
    • Covers very wide range of physical properties
Reservoir Volumetric
Quickly assess and validate hydrocarbon volumes in place


  • Monte-Carlo based efficient single tank volumetric model
  • 25 different distributions implemented
  • Modelling of correlated parameters possible
Reservoir Diagnostic
Assess past and future asset performance


  • Evaluation of large datasets enabled by proprietary technology
  • Connection of key analyses techniques
  • Statistical analysis for spatial and temporal data assessment (mapping, correlations)
  • Empirical methods (DCA)
  • Basic reservoir engineering techniques (Material balance)
  • Different oil field correlations
Understand the reservoir dynamics with respect to water movement


  • Dynamic numerical simulation to calculate water-oil displacement processes in the reservoir
  • Visualization of the water flood performance to calculate the oil recovery, water production and water injection
  • Optimization of injection spot pattern
  • Determination of water coning in vertical and horizontal wells, the critical flow rate, breakthrough time predictions and performance calculations after breakthrough
Reservoir Predictive Toolbox
Develop different mathematical methods for production forecasting


  • Empirical methods , like Decline Curves
  • Material balance models
  • Link to dynamic simulation models
Develop techno-commercial assessment for financial investment decision support (M&A, FID or Asset & Portfolio Management)

Typical Workflow:

  1. Identify clients’ key drivers (KPIs) and constraints
  2. Define scenarios (staged developments or competing concepts)
  3. Scheduling, production, OPEX/CAPEX
  4. Single/multiple phases with dependencies
  5. Setup and calibrate fiscal model (e.g. corporate Excel FM)
  6. Identify/define uncertain parameters: includes ranges, distributions and dependencies
  7. Conduct numerical assessment
  8. Carry out prediction, uncertainty assessment and optimization

Benchmark phases or competing scenarios

Reservoir Catalogue
Categorize the oil and gas reservoir in complexity indices. The advantage is an objective classification of the prospect from a geological and engineering standpoint.