Oil in the clasts do not contribute towards recoverable reserves
In FDP the clast volume has been excluded from the recoverable reserves
The uncertainty in the estimated volume of clasts and their porosity leads to a high degree of uncertainty in the view on ‘Net Volume’.
Porosity Model Recoverable volume BUT THE EFFECTIVE POROSITY IS NOT THE TRUE POROSITY OF THE MATRIX NTG is estimated using a porosity cut-off
Porosity of Clast & Impact on NTG 0 0.2 0.4 0.6 0.8 1 PHI CLAST PHIT ERROR Clast Vol PHI Cut NTG 6% 8% 10% -10% -2% +10% +2% 3.7% 6.7% 9.7% 0% 0% The effective porosity calculated depends on the clast porosity. A Porosity cut-off combined with different estimates of porosity leads to different NTG values The Porosity cutoff depends on the porosity of the clasts Since an increase in the clast volume decreases the effective porosity, the matrix porosity is underestimated and a lower porosity cutoff is required.
Probability Distributions Unit 2 P90 = 0.03 P50 = 0.21 P10 = 0.61 But what does this mean ? I am most confident that I have a NTG less than 0.03. But this is an economic producing oil field. The uncertainty range is so large it tells me nothing about reality.
Saturation exponent, cementation factor, Rw and Co-Cw used for water saturation calculation are not in agreement with measured data. Partly because of lack of sufficient high quality core data from xxxx. This will be addressed with recent conventional core and sidewalls that we have recovered. The uncertainty of +/- 5% in water saturation calculation needs to improve as much as possible once we get results of SCAL measurements in progress .
Is +/- 5% reasonable
Is it +/-5 % s.u. or +/- 5% of the value.
What is the saturation anyway
Lets spend 2 years and 200,000 USD collecting SCA data to reduce the uncertainty to +/- 2%
Uncertainty: The lack of complete certainty, that is, the existence of more than one possibility. The "true" outcome/state/result/value is not known.
Measurement of Uncertainty: A set of probabilities assigned to a set of possibilities. Example: "There is a 60% chance this market will double in five years“
Risk: A state of uncertainty where some of the possibilities involve a loss, catastrophe, or other undesirable outcome
Measurement of Risk: A set of possibilities each with quantified probabilities and quantified losses. Example: "There is a 40% chance the proposed oil well will be dry with a loss of $12 million in exploratory drilling costs".
Frequentists talk about probabilities only when dealing with well defined random experiments. The probability of a random event denotes the relative frequency of occurrence of an experiment's outcome, when repeating the experiment (i.e tossing a coin, rolling a dice).
Bayesians , however, assign probabilities to any statement whatsoever, even when no random process is involved. Probability, for a Bayesian, is a way to represent an individual's degree of belief in a statement, given the evidence.
Model Based Approach Subsurface Model 1 Uncertainty Parameter 1 Uncertainty Parameter 2 Uncertainty Parameter 3 Uncertainty Parameter n Monte-Carlo Rules For Dependency Outcome 1 Outcome 2 VOI New Data Risk(s) Acceptable Subsurface Model 2 Subsurface Model n Model Risk(s) no Model valid for Project Decision Gate yes Project Economics Note: different models Can produce different risks. Requires roll-up of models And simulation on a lower resolution