CN102033247B - Method for calculating apparent formation water resistivity spectrum and parameters by point-by-point scale electrical imaging data - Google Patents

Abstract

The invention relates to a method for calculating a resistivity spectrum and parameters of apparent formation water by point-by-point graduation electric imaging data; point-by-point calibration: aligning the electrical imaging data with the shallow resistivity depth with a logging data editing tool; calculating the average current value of the electric imaging data image; for each image frame, calculating a scale coefficient by using the conductivity values corresponding to the shallow resistivity values of the same depth points; calculating the apparent formation water resistivity spectrum of the electrical imaging data: the electric imaging through the shallow resistivity scale is substantially a conductivity image of a well wall washing zone, and the apparent formation water resistivity of one pixel point of electric imaging data is defined; calculating the apparent formation water resistivity spectrum parameters of the electrical imaging data: introducing the degree of deviation of a main peak from a base line in a mean expression apparent formation water resistivity distribution spectrum; expressing the width of the apparent formation water resistivity distribution spectrum by using variance; the shallow resistivity point-by-point scale electrical imaging data are applied, the electrical imaging data apparent formation water resistivity spectrum is calculated, and the mean value and the variance of the apparent formation water resistivity spectrum are extracted to evaluate the reservoir fluid property, so that the method has a remarkable application effect.

Description

A kind of pointwise scale electricity imaging data is calculated the method for apparant formation water resistivity spectrum and parameter

Technical field

The present invention relates to the logging technology of petroleum geology exploration, groundwater exploration.Particularly a kind of electric imaging logging data that is used for measuring according to oil well logging is discerned carbonate reservoir, the method for igneous reservoirs and low-porosity crack property sandstone reservoir fluid properties.

Background technology

The electric imaging logging appearance measures near the well stratum with the microresistivity image information data of change in depth, the variation of many curves reflection stratum microconductivities of measurement through being installed in button-electrode on the pole plate in pit shaft.Because the conductivity of different geologic bodies is different near the borehole wall, thereby Image Logging Data is with geological phenomenons such as near the bedding on the stratum form reflection borehole wall of image, crack, corrosion holes.The resistivity of mud stone shale band is low, the corrosion hole, and also the resistivity than matrix rock is low for the geological phenomenon resistivity relevant with reservoir such as crack.For expressing these different geological phenomenons, on the image of imaging data, express with various colors.Light color expression low conductivity, dark expression high conductivity.

Electricity imaging data will be carried out according to following steps in formation evaluation: the hole deviation of measuring during 1. according to well logging, magnetic azimuth, logging speed, data gain etc. are proofreaied and correct raw data; 2. because the button-electrode of electric imaging logging appearance system is a non-focusing electrode system, just its measured value only with the borehole wall near the proportional variation of conductivity of geologic body, thereby to demarcate with the shallow resistivity well-log information.The application of 3. electric imaging data.

Shallow resistivity is the important step that actual quantification is analyzed to the demarcation of electricity imaging data.Existing shallow resistivity scaling method is the piecewise linearity method.At first calculate an average current curve, carry out degree of depth coupling with this average current curve and shallow resistivity curve according to Image Logging Data; Corresponding according to degree of depth match point then log value is a horizontal ordinate with the average current, and shallow resistivity is that ordinate is drawn X plot.On X plot, obtain a piecewise linear relationship through man-machine interaction.At last, according to the convert conductivity value of this piecewise linear relationship with original measurement.The problem one that this method exists is that the more software of step realizes that workload is big, the 2nd, and the scale effect of imaging data depends on the sectional linear fitting effect.And the quality of calibration results directly influences electricity imaging data effect on this basis.

In the application facet of electricity imaging data, present great majority are used the qualitative evaluation aspect that mainly concentrates on reservoir, like crack identification, stratigraphic dip explanation etc.; Aspect the reservoir quantitative evaluation, the work of seeing has PorSpect ⁽¹⁾The factor of porosity analysis of spectrum is used to estimate primary crack and secondary pores, fracture width calculating etc.

Summary of the invention

The objective of the invention is to propose a kind of, calculate the method for looking local water spectrum and spectrum average and variance according to calibration results and discern low-porosity carbonate reservoir, igneous reservoirs, low-porosity crack sandstone reservoir fluid properties with shallow resistivity data pointwise scale electricity imaging data.

Pre-service for the electric imaging logging data; More in order to overcome the step that existing shallow resistivity data scale electricity imaging document method exists; The software work amount reaches problems such as scale effect greatly; Invented the method for shallow resistivity pointwise scale imaging data, and the method evaluation properties of fluid in bearing stratum that calculates electric imaging data apparant formation water resistivity spectrum and parameter on this basis.

1 pointwise scale method step

(1) with the well-log information edit tool form images data and the shallow resistivity degree of depth of electricity drawn together;

(2) average current value of calculating electricity imaging source map picture;

$C_{\mathrm{aver}}\left(\mathrm{dep}\right)=\underset{i=1}{\overset{n_i}{\mathrm{\Σ}}}\underset{j=1}{\overset{n_j}{\mathrm{\Σ}}}\underset{k=1}{\overset{n_k}{\mathrm{\Σ}}}C(j,k,i)/(n_i\·n_j\·n_k)---\left(1\right)$

N in the formula _iBe counting on the frames images degree of depth; n _jBe the pole plate number of imager, different instruments is different; n _kBe the button number of each pole plate of instrument, different instruments is different.(j, k i) are the measurement current value of the i depth point j pole plate k button of frames images to C; C _Aver(dep) be the average current that calculates.

(3) to each frames images (depth point of conventional logging data), the conductivity value corresponding by same depth point shallow resistivity value calculates a calibration factor;

$\mathrm{Coef}\left(\mathrm{dep}\right)=\frac{1000}{\mathrm{RS}\left(\mathrm{dep}\right)}/C_{\mathrm{aver}}\left(\mathrm{dep}\right)---\left(2\right)$

C in the formula _Aver(dep) be the average current that (1) formula is calculated; RS (dep) is the shallow resistivity log value of the corresponding degree of depth; Coefi (dep) is the calibration factor of the corresponding degree of depth of imaging source map frame.

(4) with the imaging data of a depth point of calibration factor scale corresponding diagram frame;

C_scale(j，k，i)＝Coef(dep)*C(j，k，i) (3)

(j, k i) are the j pole plate of input image frame to C in the formula, k button, the measurement current value of i depth point; C_scale (j, k, i) the scale pixel value of corresponding point.

Pointwise scale step by top can know that the advantage of this method is that the scale process does not need manual intervention, directly with the shallow resistivity data of depth match electricity imaging data is carried out careful scale.The prerequisite of this scale method is electric imaging data and shallow resistivity depth match, has relatively high expectations for depth match.

The apparant formation water resistivity spectrum of 2 electric imaging data is calculated

Come down to the conductivity map picture of borehole wall flushed zone through the electricity imaging of shallow resistivity scale.Define the apparant formation water resistivity of a pixel of electric imaging data.

R _wa(j，k，i)＝φ(dep)[RS(dep)·C_scale(j，k，i)] ^1/m(dep)/C_scale(j，k，i)

(4)

(i, j k) are the conductivity value of i depth point j pole plate k button through scale, s/m to C_scale in the formula; M (dep) is the cementation exponent in the Archie equation, adopts three porosity Model Calculation [ref 3]; RS (dep) is a flushed zone resistivity.The total porosity that φ (dep) calculates for conventional logging.Can calculate the apparant formation water resistivity value of electric each pixel of imaging data according to (4) formula.

For a frames images, then can obtain the apparant formation water resistivity spectrum according to its histogram of result of calculation primary system meter of each pixel, be used to discern fluid properties.

The apparant formation water resistivity spectrum calculation of parameter of 3 electric imaging data

For the difference on quantitative evaluation oil gas interval and the water layer section apparant formation water resistivity distribution profile, main peak departs from the degree of baseline in the introducing average expression apparant formation water resistivity distribution profile; Express the width (dispersiveness) of apparant formation water resistivity distribution profile with variance (second moment).It is following that depth point apparant formation water resistivity is composed equal value defined

$\stackrel{\‾}{R_{\mathrm{wa}}}=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{R}_{\mathrm{wai}}{P}_{R_{\mathrm{wai}}}/\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{P}_{R_{\mathrm{wai}}}---\left(5\right)$

R in the formula _WaiBe the apparant formation water resistivity value, Be that corresponding apparant formation water resistivity is R _WaiFrequency (pixel number).Apparant formation water resistivity spectrum variance

${\mathrm{\σ}}_{R_{\mathrm{wa}}}=\sqrt{\frac{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{P}_{R_{\mathrm{wai}}}{(R_{\mathrm{wai}}-\stackrel{\‾}{R_{\mathrm{wa}}})}^2}{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{P}_{R_{\mathrm{wai}}}}}---\left(6\right)$

Can find out that by above-mentioned definition the average that apparant formation water resistivity distributes is expressed the degree that departs from baseline; Variance has been expressed the dispersion degree (width of main peak) that the apparant formation water resistivity spectrum distributes

The characteristic of the apparant formation water resistivity spectrum of hydrocarbon zone is " value is big and wide "; The characteristic of the apparant formation water resistivity spectrum of water layer is " value is little and narrow ".For the average and the variance of a certain depth calculation, hydrocarbon zone is that the both increases; The characteristic that the water layer both is little.

Invention is also used the different electricity imaging data of many mouthfuls of wells of different regions, and effect is remarkable.

Use shallow resistivity pointwise scale electricity imaging data, calculate electric imaging data apparant formation water resistivity spectrum on this basis, the average of extraction apparant formation water resistivity spectrum and variance are estimated properties of fluid in bearing stratum has significant effect.

Description of drawings

Fig. 1 is an apparant formation water resistivity spectrum discrimination fluid properties synoptic diagram.Wherein, a figure is the Rwa spectrum synoptic diagram of water layer; B figure is the Rwa spectrum synoptic diagram of oil reservoir.Ordinate P is a frequency in the accompanying drawing 1, and horizontal ordinate is the size of apparant formation water resistivity.

Fig. 2 pointwise scale electric imaging logging data is calculated the process flow diagram of electricity imaging apparant formation water resistivity spectrum and parameter.

Embodiment

At Si Lunbeixie Geoframe ⁽¹⁾3.8 environment and Cifsun ⁽⁴⁾Realize the foregoing invention content in the environment, developed the corresponding program module.

At Geoframe ⁽¹⁾The environment performing step is shown in accompanying drawing 2.

1) at Geoframe ⁽¹⁾Load routine and Image Logging Data in the software;

2) utilize three porosity Model Calculation conventional logging data factor of porosity Φ (dep) and m (dep) value;

3) use Geoframe ⁽¹⁾BorEID in the software ⁽¹⁾Module is carried out pre-service to the imaging data;

4) realize formula (1) (2) (3) (4) (5) on the basis of calculating and result in front

(6) program module;

5) result apparant formation water resistivity spectrum and parameter are carried out statistical computation and drawing.

Wherein realize above-mentioned steps 4) mode following.

I) to the FMI Data Processing, n in formula (1) _k=8, n _j=24, n _i=50; Realize formula (2), (3), (4) then.

II) statistics 8*24*50 point α R _Wa(j, k, histogram i), α=3.3 are coefficient, obtain a depth point apparant formation water resistivity spectrum

III) by formula the average and the variance of a depth point apparant formation water resistivity spectrum

added up in (5) and (6).

IV) draw result of calculation such as accompanying drawing 2, accompanying drawing 3.The 4th road is an imaging data apparant formation water resistivity spectrum, and the 5th road is the average and the variance of apparant formation water resistivity spectrum.

V) to the EMI Data Processing, n in formula (1) _k=6, n _j=25, n _i=50; Realize formula (2), (3), (4) then.

VI) statistics 6*25*50 point α R _Wa(j, k, histogram i), α=3.3 are coefficient, obtain a depth point apparant formation water resistivity spectrum

VII) by formula the average and the variance of a depth point apparant formation water resistivity spectrum added up in (5) and (6).

(note:

(1) Geoframe, FMI, BorEID, PorSpect, the Schlumberge house mark

(2) EMI, Haliburton Logging Services house mark

(3) STARII, Atlas Wireline Services house mark

(4) Cifsun, MCI, the CNPC house mark)

Claims (1)

1. pointwise scale electricity imaging data is calculated the method for apparant formation water resistivity spectrum and parameter, it is characterized in that:

1) pointwise scale step

(1) with the well-log information edit tool form images data and the shallow resistivity degree of depth of electricity drawn together;

(2) average current value of calculating electricity imaging source map picture;

N in the formula _iBe counting on the frames images degree of depth; n _jBe the pole plate number of imager, different instruments is different; n _kBe the button number of each pole plate of instrument, different instruments is different; (j, k i) are the measurement current value of the i depth point j pole plate k button of frames images to C; C _Aver(dep) be the average current that calculates;

(3) to each frames images, the conductivity value corresponding by same depth point shallow resistivity value calculates a calibration factor;

C in the formula _Aver(dep) be the average current that (1) formula is calculated; RS (dep) is the shallow resistivity log value of the corresponding degree of depth; Coef (dep) is the calibration factor of the corresponding degree of depth of imaging source map frame;

(4) with the imaging data of a depth point of calibration factor scale corresponding diagram frame;

C_scale(j，k，i)＝Coef(dep)*C(j，k，i) (3)

(j, k i) are the j pole plate of input image frame to C in the formula, k button, the measurement current value of i depth point; (j, k i) are the scale pixel value of corresponding point to C_scale;

2) apparant formation water resistivity of electric imaging data spectrum is calculated

The electricity imaging of process shallow resistivity scale comes down to the conductivity map picture of borehole wall flushed zone, defines the apparant formation water resistivity of a pixel of electric imaging data;

R _wa(j，k，i)＝φ(dep)[RS(dep)·C_scale(j，k，i)] ^1/m(dep)/C_scale(j，k，i)(4)

(j, k i) are the conductivity value of i depth point j pole plate k button through scale, s/m to C_scale in the formula; M (dep) is the cementation exponent in the Archie equation, adopts the three porosity Model Calculation; RS (dep) is a flushed zone resistivity; The total porosity that φ (dep) calculates for conventional logging; Can calculate the apparant formation water resistivity value of electric each pixel of imaging data according to (4) formula;

For a frames images, then can obtain the apparant formation water resistivity spectrum according to its histogram of result of calculation primary system meter of each pixel, be used to discern fluid properties;

3) apparant formation water resistivity of electric imaging data spectrum calculation of parameter

Main peak departs from the degree of baseline in the introducing average expression apparant formation water resistivity distribution profile; Express the width of apparant formation water resistivity distribution profile with variance, it is following that depth point apparant formation water resistivity is composed equal value defined

R in the formula _WaiBe the apparant formation water resistivity value, Be that corresponding apparant formation water resistivity is R _WaiFrequency, i.e. pixel number, apparant formation water resistivity spectrum variance

Images