petrophysical uncertainties do they really matter? · objectives of petrophysics •to assess the...
TRANSCRIPT
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Petrophysical UncertaintiesDo They Really Matter?
A brief discussion on uncertainties
in petrophysical evaluations
Ko Ko Kyi
Retired Principal Petrophysicist
28 April 2019
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Uncertainties in Resource Assessment
• Geophysical uncertainties
• Geological uncertainties
• Petrophysical uncertainties• Uncertainties in measurements
• Uncertainties in interpretation
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Ref: Schlumberger Oilfield Review
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Objectives of Petrophysics
• To assess the presence of hydrocarbon accumulation in exploration areas
• To provide input parameters for hydrocarbon resource assessment
• To confirm the presence of hydrocarbons and quantify their volumes in development wells
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Hydrocarbon Resource Assessment
• Calculation of Hydrocarbon Initially In Place
HIIP = GBV x N/G x F x (1-Sw) x 1/FVF
Where, HIIP = hydrocarbon initially in place
GBV = gross bulk volume of rock
N/G = net to gross ratio
F = porosity
Sw = water saturation
FVF = formation volume factor
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Hydrocarbon Volume Calculation
In the following equation:
HIIP = GBV x N/G x F x (1-Sw) x 1/FVF
Three main parameters, namely N/G, F and Sw are provided by petrophysicists
Other important parameters provided by petrophysicists are fluid type, fluid contacts and permeability estimates
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Effects of Uncertainties in Parameters on Resource Assessment
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Definitions of Petrophysical Parameters
• Net to Gross = Net Thickness/Gross Thickness
• Porosity = (Total Pore Volume)/(Total Rock Volume)
• Sw = (Water filled porosity)/(Total porosity)
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Petrophysical Definitions
• Gross Interval Thickness
Base of Interval minus Top of Interval
• Gross Sand Thickness
The sum of all thicknesses in the Sand Unit , meeting a certain clay volume Vcl cutoff criterion
• Net Sand Thickness
The sum of all thicknesses in the Gross Sand,
meeting a certain porosity F cutoff criterion
• Net Pay Thickness
The sum of all thicknesses in the Net Sand, meeting
a certain water saturation Sw cutoff criterion
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Petrophysical Dependencies
• Gross Sand thickness is dependent on clay volume Vcl cutoff
• Net Sand thickness is dependent on clay volume Vcl and porosity F cutoffs
• Net Pay thickness is dependent on clay volume Vcl , porosity F and water saturation Sw cutoffs
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Petrophysical Interdependencies
• Net to gross ratio N/G, net sand, net pay, average porosity and average water saturation are all inter-related
• A change in one parameter, e.g. net sand, results in changes in other related parameters, e.g. average porosity and average water saturation of the net sand
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Measurement Uncertainties
Well Logs
• Errors in depth measurements due to cable wear, stretching, reduction in cable diameter, sticky hole, etc.
• Errors in depth due to pipe stretching, pipe tally for MWD/LWD
• Errors in True Vertical Depth conversion using survey data and different methods of conversion
• Errors in tool calibrations
• Intrinsic tool errors, due to tool limitations
• Algorithms used to convert measured raw data into output data
• Hostile borehole environment for logging tools
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Ref: Schlumberger Oilfield Review
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Ref: Schlumberger Oilfield Review
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Depth Measurement Accuracy
• Both drill pipe and wireline cable suffer from stretch and inaccuracies in measuring well depth
• This uncertainty becomes greater with increasing depth
and well deviation
• For a vertical well of 3500 m depth, measured depth at TD
has an accuracy of about 2 meters
• For a deviated well of 3500 m depth and 50 degrees deviation at bottom, the inaccuracy may increase to about
5 meters
• Well surveys measure borehole deviation and azimuth and produce X and Y lateral displacements only, they do not provide absolute vertical depth measurements
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Well Deviation Survey Accuracy
• Magnetic Survey Tools - typical lateral borehole uncertainties;
14 m per 1000 m in a vertical well and 20 m per 1000 m in a
70 degrees deviated well
• Gyro Survey Tools – typical lateral borehole uncertainties:
1.5 m per 1000 m in a vertical well and 8 m per 1000 m in a
70 degrees deviated well
• FINDS (Schlumberger) – utilizes highly accurate accelerometers and double integrate the accelerations to determine absolute distance moved by tool during survey:
accuracy of 0.5 m per 1000 m regardless of deviation
• There may be more accurate systems which have become commercial since this presentation was made.
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Borehole Position Uncertainty
Effects of Borehole Position Uncertainty
• Well Safety – drilling of relief well to intercept another well;
well collision avoidance in densely drilled areas
• Mapping – uncertainties in true vertical depths of reservoir horizons can lead to serious errors in maps; errors in fluid contacts may lead to wrong judgments on faults
• Geosteering – accurate measurement of TVD is required
• Pressure/gradient determination – requires accurate TVD
• Legal implications – accurate TVD to drill within national boundaries; unitization and equity determination issues
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Mitigating Factors
Depth Measurements
• Logging contractors use best industrial practices to correct for depth measurement errors due to cable and pipe stretch
• Although absolute depth measurements have intrinsic errors, relative depths are reasonably accurate
• It is a prudent practice to incorporate uncertainties in depth measurements when computing hydrocarbon volumes
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Petrophysical Parameters
Shale Volume Vsh
• Shale volume cutoff is used to determine gross sand
• Sensitive to method of calculation used
• Several methods of computing shale volume
• Simplest and easiest method to compute Vsh is from GR log
Vsh = (GR – GRmin)/(GRmax – GRmin)
Where, GR = Gamma Ray log reading
GRmax= Maximum GR log reading
GRmin = Minimum GR log reading
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Ref: Schlumberger Oilfield Review
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Ref: Schlumberger Oilfield Review
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Parameters for Shale Volume Simulation
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Vsh Simulation Summary
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Vsh Frequency Distribution
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Vsh Cumulative Distribution
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Petrophysical Parameters
Porosity F
• Porosity cutoff is used to determine Net Sand
• Several methods of computing porosity from logs
• Preferred method is to compute porosity using density log
F = (rb – rma)/(rf – rma)
Where, rb = bulk density of rock
rma = matrix density
rf = fluid density
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Parameters for Porosity Simulation
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Porosity Simulation Summary
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Porosity Frequency Distribution
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Porosity Cumulative Distribution
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Porosity Sensitivity Analysis Results
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Petrophysical Parameters
Water saturation Sw
• Sw cutoff is used to determine Net Pay
• Several models can be used to compute Sw
• Simplest model is Archie’s equation for clean sand
Swn = (aRw)/(Fm x Rt)
Where, n = saturation exponent
a = Archie’s constant
m = cementation exponent
Rw= resistivity of formation water
Rt= true resistivity of formation
F = formation porosity
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Parameters for Sw Simulation
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Sw Simulation Summary
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Sw Frequency Distribution
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Sw Cumulative Distribution
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Sw Sensitivity Analysis Results
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Input Parameters for Sw Modelling
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Tornado Chart for Sw Computation
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Frequency Distribution of Modelled Sw
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Ref: Schlumberger Oilfield Review
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Ref: Schlumberger Oilfield Review
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Measurement Uncertainties
Core Data
• Alteration of formation properties due to dissimilar saturantproperties
• Measurements done under laboratory conditions may not truly represent those at reservoir conditions
• Basic assumptions used in core measurements may not truly represent the actual formation properties
• Errors in best guess estimation of confining pressures used in measurements simulating overburden condition
• Errors in actual measurements
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Uncertainties in Core Analysis
Results of study by the Society of Core Analysts
• Only four out of 17 core analysis laboratories mixed the correct brine solution with required salinity of 100,000 ppm NaCl
• Even when provided with premixed brine, laboratories reported different resistivity values
• The saturation exponent n and cementation exponent m, obtained using different methods, show a fair amount of scatter, between 1.6 to 2.1
Ref: Pierre Berger, Schlumberger
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Ref: Pierre Berger, Schlumberger
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Ref: Pierre Berger, Schlumberger
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Sensitivity Analysis for m and n
To study the effects of errors in m and n values on water saturation determination, Archie’s equation can be expressed as follows for changes in m and n:
(DSw/Sw)m = -(Dm/n) * (ln F) keeping n constant
(DSw/Sw)n = -(Dn/n) * (ln Sw) keeping m constant
The effects of changes of m and n values on Sw are shown on the following plots
Ref: Pierre Berger, Schlumberger
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The effect of rock porosity as relative error in water saturation determination
(DSw/Sw) caused by relative deviations in cementation exponent (Dm/n)
Ref: Pierre Berger, Schlumberger
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The effect of water saturation as relative error in water saturation determination
(DSw/Sw) caused by relative deviations in saturation exponent (Dn/n)
Ref: Pierre Berger, Schlumberger
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Effects of m and n values
Effects of the changes in m and n values
• An exact knowledge of m and n values are crucial for the determination of water saturation Sw
• The biggest error in saturation determination is likely to come from inaccurate estimate of m and n values
• The effect becomes worse in shaly formations as there is an apparent decrease in the slope of the Resistivity Index (I) to Sw response
• There can be several inaccuracies in the m and n values measured in laboratories
Ref: Pierre Berger, Schlumberger
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residual oil
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Handling Uncertainties
• Recognize the existence of uncertainties• There are no unique solutions in petrophysics
• Identify major uncertainties and their effects• Determine which uncertainties have biggest effects
• Do sensitivity analysis on the impact of uncertainties
• Mitigate uncertainty effects by using statistics• Provide range of values for petrophysical parameters to
account for various uncertainties
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Recommended Practice
For single well average parameter
• Find average value (e.g. FAVG ) and standard deviation ( s ) of the parameter of interest for the well
• Uncertainty of parameter = 2 x s
• Minimum value FMIN = FAVG - (2 x s)
• Maximum value FMAX = FAVG + (2 x s)
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Recommended Practice
For multi well average parameter in a field
• Find average value (e.g. POR) and standard deviation (PORSD) of the parameter for the wells (n) in the field
• Uncertainty (UNC) in POR = SQRT((PORSD)2 / (n + s2))
• Minimum value PORMIN = POR - (2 x UNC)
• Maximum value PORMAX = POR + (2 x UNC)
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Some Common Practices
Most companies handle uncertainties in petrophysical parameters in the following ways:
For probabilistic method of resource assessment, a range of input parameters are used:
• Minimum, Most Likely and Maximum Values
• P15, P50 and P85 values
• P10, P50 and P90 values
In geostatic models, several porosity, water saturation curves etc. for different scenarios are used in Monte Carlo simulation to compute a range of hydrocarbon volumes.
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Ref: Schlumberger Oilfield Review
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The 50-50-90 Rule
Anytime you have a 50-50 chance of getting something right, there's a 90% probability that you'll get it wrong
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Thank You!!