CN101887132A - Method for quantificationally predicting sandstone reservoir fluid saturation by combining well and seism - Google Patents
Method for quantificationally predicting sandstone reservoir fluid saturation by combining well and seism Download PDFInfo
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Abstract
The invention discloses a method for quantificationally predicting sandstone reservoir fluid saturation by combining a well and seism in geophysical prospecting for petroleum. The method comprises the following steps of: acquiring and processing seismic data and log data to obtain each parameter curve; respectively determining the relationships among the shale content, the porosity and an elastic parameter of the well; establishing prediction models of the shale content and the porosity; calculating a pore volume modulus and a dry rock volume modulus to establish a modulus prediction model; establishing an effective reservoir water saturation prediction model; performing prestack seismic inversion by utilizing prestack seismic trace gathers and the log data to obtain an inversion data volume of each elastic parameter; calculating the dry rock volume modulus to solve the pore volume modulus by the obtained elastic inversion volume; and solving the water saturation by using the pore volume modulus. In the method, prestack seismic data and the log data are fully utilized for quantificationally predicting reservoir saturation; and good geological effects on predicting oil and gas saturation are achieved.
Description
Technical field
The present invention relates to the geophysical prospecting for oil technology, specifically is a kind of method of the quantificationally predicting sandstone reservoir fluid saturation by combining well and seism based on the volume of voids modulus.
Background technology
Utilize seismic data the pore fluid of underground rock is predicted it is the target of seismic work.One of means that AVO (amplitude changes with geophone offset) attributive analysis directly detects as oil gas, once in bright spot and the detection of flat spot type gas reservoir, brought into play vital role, yet the AVO attributive analysis is subjected to tuning influence, can only carry out qualitative description to reservoir fluid, and has a lot of traps.Seismic inversion, the especially appearance of pre-stack seismic inversion technique make that utilizing seismic data that the reservoir pore space fluid is carried out quantitative forecast becomes possibility.In recent years, utilize geological data to carry out petroleum-gas prediction and become a focus, but main achievement in research still concentrates on the qualitative description and the prediction aspect of convection cell, as the AVO intersection that Ruthorford and Castanga etc. propose, the wavelet energy analysis method of propositions such as Peters etc. all can only carry out qualitative forecasting to the gas-bearing property of reservoir.Li Hongbing has carried out the gas-bearing property prediction with the wavelet scale spectrometry to Caidamu Basin gas reservoir; Sweet sharp lamps etc. have been discussed the potentiality of elastic impedance in lithology and fluid prediction in detail; Li Zongjie etc. utilize various seismic properties in system in Tahe Oilfield the oiliness of Ordovician system oil-containing reservoir to be predicted, and have obtained certain effect; Comprehensive utilization infiltration rate frequency dispersions (AVD) such as Li dignitary, dynamic power spectrum technology such as (DR) have been carried out the gas-bearing property detection to the non-homogeneous tight sand of Xu Jia river, gas field, new field gas reservoir; Li Aishan etc. have showed the application of the synchronous prestack inversion method of AVA in Shengli Oil Field Jiyang depression middle level gas reservoir is effectively discerned; Gao Jianhu etc. have proposed the application of poststack oil and gas testing technique in oil and gas detection such as comprehensive utilization effective absorption coefficient, seismic event kinetic parameter and spectral amplitude identification.
Also there are many scholars to explore domestic aspect the fluid saturation quantitative forecast, as, Zhang Eyong multiple regression procedure and more than 20 poststack seismic properties have carried out predicting (petroleum prospecting and exploitation to the sandstone thickness and the zone of interest of study area, 2000,27 rolled up for 1 phases), and obtained effect preferably.But because this method is based on poststack seismic properties rather than seismic inversion parameter, make this method have resolution low, the quality of seismic data is relied on shortcomings such as serious.The thinking that Li Lailin has proposed to utilize earthquake and log data to ask for static remaining oil saturation based on time-average equation (grand celebration oil geology and exploitation,, 21 3 phases of volume in 2000) has the certain experiences meaning to the remaining oil prediction in oil and gas development district.Liu Yang has proposed a kind of method and thinking (petroleum journal that utilizes geological data estimation rock porosity and fluid saturation, 2005,26 2 phases of volume), its method is at first to utilize the Changing Pattern of elastic parameters such as Gassmann Model Calculation p-and s-wave velocity, density, speed compare with factor of porosity, saturation degree, and set up the respective explanations plate, obtain elastic parameter by various inversion methods then, and with the interpretation chart comparative analysis, and then factor of porosity and saturation degree carried out the sxemiquantitative estimation, its method and thinking have certain promotion value.Jin Long etc. have proposed a kind of new method (petroleum journal based on petrophysical model and hybrid optimization algorithm while inverting factor of porosity and saturation degree, 2006,27 4 phases of volume), this method adds refutation process as constraint with factor of porosity and saturation degree, its stability and validity have been passed through the check of The model calculation, but are not applied in the actual seismic data.As seen, the method that does not also have a kind of practicality, effective quantitative forecast saturation degree at present both at home and abroad.
Summary of the invention
The object of the present invention is to provide a kind of method of the quantificationally predicting sandstone reservoir fluid saturation by combining well and seism based on the volume of voids modulus.
The present invention is achieved through the following technical solutions:
1) adopt arrangement greatly, small distance between receivers, high-density sampling is gathered high-quality geological data, seismic data is protected the width of cloth handle, and forms the common midpoint gather of fidelity;
It is to keep the AVO feature in processing procedure that the described guarantor's width of cloth of step 1) is handled.
2) gather compressional wave time difference, density, neutron, spontaneous potential or GR, resistivity conventional logging data, obtain logging trace, and processing obtains shale index, factor of porosity, saturation curves.
Step 2) described collection data is gathered the shear wave slowness curve to the well more than a bite at least.
3) obtain longitudinal and transverse wave velocity curve from compressional wave time difference, shear wave slowness curve, calculate p-wave impedance according to p-and s-wave velocity, densimetric curve, the shear wave impedance, p-and s-wave velocity is than elastic parameter curve;
The described shear wave velocity curve of step 3) utilizes Xu-White Model Calculation shear wave velocity curve when not gathering the well of shear wave slowness curve.
4) utilize multivariate statistical method to determine relation between shale index and factor of porosity and the elastic parameter respectively at well point place, set up the forecast model of following shale index and factor of porosity:
V
Sh＝f
sh(L
1，L
2，L
3，...) (1)
φ＝f
φ(L
1，L
2，L
3，...) (2)
In the formula: V
ShThe expression shale index, φ represents factor of porosity, f
Sh, f
φAll represent the multivariate function, independent variable is that elastic parameter, dependent variable are respectively shale index and factor of porosity, L
1, L
2, L
3... L
nBe the elastic parameter curve;
5) adopt following formula to calculate volume of voids modulus and dry rock bulk modulus:
K
d＝K
sat-K
p (4)
In the formula: K
SatThe bulk modulus of representing complete saturated rock, K
dThe bulk modulus of expression dry rock, K
pExpression hole bulk modulus, φ represents factor of porosity, K
sThe bulk modulus of expression rock matrix, K
fThe bulk modulus of expression pore fluid;
6) utilize dry rock bulk modulus and elastic parameter curve, set up the forecast model of dry rock bulk modulus:
K
d＝f
kd(L
1，L
2，L
3，...) (5)
In the formula: L
1, L
2, L
3... L
nBe elastic parameter curve, f
KdExpression is that independent variable, dry rock bulk modulus are the multivariate function of dependent variable with the elastic parameter;
7) utilize multiple regression procedure to set up the forecast model of water saturation in effective reservoir:
S
w＝f
sw(K
p，L
4，L
5，...) (6)
In the formula: L
1, L
2, L
3Expression elastic parameter curve, S
wBe water saturation, f
SwExpression is that independent variable, water saturation are the multivariate function of dependent variable with the elastic parameter.
8) utilize pre-stack seismic road collection and well-log information to carry out the pre-stack seismic inverting, obtain the inverting data volume of various elastic parameters, and utilize formula (1) and formula (2) to calculate shale index and factor of porosity data volume from the elastic parameter inversion data volume;
9) forecast model that utilizes step 5) to set up calculates the dry rock bulk modulus from step 8) gained elastic parameter inversion data volume;
10) utilize inverting elastic parameter data volume to ask the bulk modulus of saturated rock, and then ask volume of voids modulus K by formula (4)
p
11) utilize formula (6) to ask water saturation S from the volume of voids modulus
w
The present invention has made full use of pre-stack seismic data and well-log information, has realized the quantitative forecast to the reservoir pore space fluid saturation, and on-the-spot test has good geological effect to oil-containing, gas saturation prediction.
Description of drawings
Fig. 1 is the technology of the present invention process flow diagram;
Fig. 2 for the present invention in shale index, factor of porosity and the saturation curves of somewhere well logging interpretation with by the comparison diagram of the curve of elastic parameter prediction; (solid line is a measured curve, and dotted line is a prediction curve)
Fig. 2 (a) is shale index prediction effect figure;
Fig. 2 (b) is the porosity prediction design sketch;
Fig. 2 (c) is water saturation prediction effect figure;
Fig. 3 (a) protects the width of cloth for certain survey line and handles the CDP road collection that obtains;
Fig. 3 (b) is the stack result of CDP road collection shown in Fig. 3 (a);
Fig. 4 (a) is certain survey line shale index sectional view;
Fig. 4 (b) is for laterally following the trail of effective reservoir of gained according to the shale index section;
Fig. 4 (c) is the factor of porosity section that calculates at effective reservoir;
Fig. 5 is the volume of voids modulus sectional view of certain survey line;
Fig. 6 is certain survey line water saturation sectional view;
Fig. 7 is certain survey line gas saturation and factor of porosity product sectional view.
Embodiment
The present invention utilizes well logging and pre-stack seismic data quantitative forecast sandstone reservoir fluid saturation, at first by the water saturation forecast model of well-log information foundation based on elastic parameter, utilize the pre-stack seismic inverting to obtain required elastic parameter data volume then, calculate water saturation in conjunction with forecast model, realize the quantitative forecast of reservoir fluid.Fig. 1 is the technology of the present invention process flow diagram.
The present invention will be further described below in conjunction with example:
1) adopt arrangement greatly, small distance between receivers, high-density sampling is gathered high-quality geological data, seismic data is protected the width of cloth handle, and forms the common midpoint gather of fidelity, as shown in Figure 3.Fig. 3 (a) and (b) be respectively certain and distinguish certain survey line and protect CDP road collection and corresponding stacked section after width of cloth is handled.Zone of interest is 8 sections in a box, and its corresponding volume lineups in end, top mark (among the patent figure color can not be arranged, interchangeable saying) in Fig. 3 (b).
2) gather this district's compressional wave time difference, density, neutron, spontaneous potential or GR, resistivity conventional logging data, obtain logging trace, and explained shale index, factor of porosity, saturation curves; This area has Liang Koujing that the shear wave slowness curve of actual measurement is arranged.
3) surveying shear wave slowness with two causes for gossip is constraint, the shear wave slowness curve of all the other wells that utilized the Xu-White Model Calculation.According to compressional wave time difference, the longitudinal and transverse wave velocity curve of shear wave slowness curve calculation, and then calculate p-wave impedance, shear wave impedance, p-and s-wave velocity according to p-and s-wave velocity, densimetric curve and the elastic parameter curve such as compare.
4) utilize multivariate statistical method to determine relation between shale index and factor of porosity and the elastic parameter respectively at well point place, set up the forecast model of following shale index and factor of porosity.
Shale index (V
Sh) available following nonlinear function calculating:
V
Sh＝f(V
p，V
s，ρ)，R＝0.836 (7)
In the formula: V
ShThe expression shale index, V
pThe expression velocity of longitudinal wave, V
SThe expression shear wave velocity, ρ represents density, R represents related coefficient.
In effective reservoir, factor of porosity can directly carry out linear transformation from density and obtain:
φ＝85.642-30.83ρ，R＝0.79 (8)
In the formula: φ represents factor of porosity, and ρ represents density, and R represents related coefficient.
Fig. 2 (a) and Fig. 2 (b) are respectively the comparison with result of log interpretation of predicting the outcome of shale index and factor of porosity, and both coincide fine, illustrates predicting the outcome of well point shale index and factor of porosity reliably, and this accurately predicts for water saturation and lays a good foundation.
5) calculate volume of voids modulus (K according to formula (3)
p), and then according to formula (4) calculating dry rock bulk modulus (K
d).
6) utilize dry rock bulk modulus and elastic parameter curve, set up the forecast model of dry rock bulk modulus:
K
d＝30.26+0.1721V
sh-101.37φ，R＝0.80 (9)
In the formula: K
dBe dry rock bulk modulus, V
ShBe shale index, φ is a hole, and R is a related coefficient;
7) by statistics, the relation of water saturation and volume of voids modulus has difference slightly in local area I class sandstone and the II class sandstone,
In I class sandstone:
S
w＝20.42K
p+18.26，R＝0.93 (10a)
In II class sandstone:
S
w＝14.11K
p+32.95，R＝0.79 (10b)
According to formula (10a) and (10b) prediction saturation curves and well logging interpretation saturation curves relatively see Fig. 2 (c), the two is the variation tendency unanimity not only, and numerical value is close, has illustrated that the saturation degree forecast model of setting up is effective.
8) utilize pre-stack seismic road collection and well-log information to carry out the pre-stack seismic inverting, obtained the inversion result of velocity of longitudinal wave, shear wave velocity and density, and calculated p-wave impedance, shear wave impedance, p-and s-wave velocity and elastic parameter such as compared.
By the pre-stack seismic inverting gained elastic parameter calculating of the forecast model shown in (7) by formula shale index data volume, the result is shown in Fig. 4 (a).According to the shale index section reservoir is laterally followed the trail of and to be obtained effective reservoir distribution figure, as Fig. 4 (b).At effective reservoir by elastic parameter by formula (8) calculate factor of porosity data volume, result such as Fig. 4 (c).
Fig. 4 (a) has shown the shale index curve among 4 (b), and the curve that shows among Fig. 4 (c) is a porosity curve.As seen from the figure, shale index and factor of porosity predict the outcome and logging trace coincide fine.
9) utilize forecast model shown in the formula (9) to calculate dry rock bulk modulus data volume from step 8) gained elastic parameter inversion data volume;
10) utilize inverting elastic parameter data volume to ask the bulk modulus of saturated rock, and then ask the volume of voids modulus by formula (4).Fig. 5 is for calculating volume of voids modulus sectional view, and the curve that shows among the figure is the water saturation curve.From scheming as seen, it is good with water saturation curve corresponding relation to predict the outcome, and illustrates that the volume of voids modulus section of asking can be used for the fluid prediction.
11) utilize formula (10a) and (10b) calculated the water saturation data volume, as shown in Figure 6 from the volume of voids modulus.The curve that shows among the figure is a well logging interpretation water saturation curve.As seen from the figure, earthquake prediction water saturation and well logging interpretation saturation degree are coincide good.
Press S
g=100-S
wWith water saturation (S
w) be converted into gas saturation (S
g) section, and and factor of porosity
Section multiplies each other and obtains factor of porosity saturation degree product
Section, this section is described more directly perceived than water saturation section, more effective to reservoir gas-bearing property.
Fig. 7 is gas saturation and the factor of porosity product sectional view that is calculated, and the curve that shows among the figure is the water saturation curve of well logging interpretation.According to log well in advance A and well B place zone of interest of this section is the high yield gas-bearing formation, after 150,000 sides are produced in drilling well and gas testing confirmation well A gas testing daily, though not gas testing of well B, well logging interpretation is the high-quality payzone, and predicting the outcome has obtained the check of drilling well, illustrates that prediction effect is good.
Claims (4)
1. method based on the quantificationally predicting sandstone reservoir fluid saturation by combining well and seism of volume of voids modulus is characterized in that being achieved through the following technical solutions:
1) adopt arrangement greatly, small distance between receivers, high-density sampling is gathered high-quality geological data, seismic data is protected the width of cloth handle, and forms the common midpoint gather of fidelity;
2) gather compressional wave time difference, density, neutron, spontaneous potential or GR, resistivity conventional logging data, obtain logging trace, and processing obtains shale index, factor of porosity, saturation curves.
3) obtain longitudinal and transverse wave velocity curve from compressional wave time difference, shear wave slowness curve, calculate p-wave impedance according to p-and s-wave velocity, densimetric curve, the shear wave impedance, p-and s-wave velocity is than elastic parameter curve;
4) utilize multivariate statistical method to determine relation between shale index and factor of porosity and the elastic parameter respectively at well point place, set up the forecast model of following shale index and factor of porosity:
V
Sh＝f
sh(L
1，L
2，L
3，...) (1)
φ＝f
φ(L
1，L
2，L
3，...) (2)
In the formula: V
ShThe expression shale index, φ represents factor of porosity, f
Sh, f
φAll represent the multivariate function, independent variable is that elastic parameter, dependent variable are respectively shale index and factor of porosity, L
1, L
2, L
3... L
nBe the elastic parameter curve;
5) adopt following formula to calculate volume of voids modulus and dry rock bulk modulus:
K
d＝K
sat-K
p (4)
In the formula: K
SatThe bulk modulus of representing complete saturated rock, K
dThe bulk modulus of expression dry rock, K
pExpression hole bulk modulus, φ represents factor of porosity, K
sThe bulk modulus of expression rock matrix, K
fThe bulk modulus of expression pore fluid;
6) utilize dry rock bulk modulus and elastic parameter curve, set up the forecast model of dry rock bulk modulus:
K
d＝f
kd(L
1，L
2，L
3，...) (5)
In the formula: L
1, L
2, L
3... L
nBe elastic parameter curve, f
KdExpression is that independent variable, dry rock bulk modulus are the multivariate function of dependent variable with the elastic parameter;
7) utilize multiple regression procedure to set up the forecast model of water saturation in effective reservoir:
S
w＝f
sw(K
p，L
4L
5，...) (6)
In the formula: L
1, L
2, L
3Expression elastic parameter curve, S
wBe water saturation, f
SwExpression is that independent variable, water saturation are the multivariate function of dependent variable with the elastic parameter;
8) utilize pre-stack seismic road collection and well-log information to carry out the pre-stack seismic inverting, obtain the inverting data volume of various elastic parameters, and utilize formula (1) and formula (2) to calculate shale index and factor of porosity data volume from the elastic parameter inversion data volume;
9) forecast model that utilizes step 5) to set up calculates the dry rock bulk modulus from step 8) gained elastic parameter inversion data volume;
10) utilize inverting elastic parameter data volume to ask the bulk modulus of saturated rock, and then ask volume of voids modulus K by formula (4)
p
11) utilize formula (6) to ask water saturation S from the volume of voids modulus
w
2. the method for the quantificationally predicting sandstone reservoir fluid saturation by combining well and seism based on the volume of voids modulus according to claim 1 is characterized in that it is to keep the AVO feature in processing procedure that the described guarantor's width of cloth of step 1) is handled.
3. the method for the quantificationally predicting sandstone reservoir fluid saturation by combining well and seism based on the volume of voids modulus according to claim 1, step 2) described collection data is gathered the shear wave slowness curve to the well more than a bite at least.
4. the method for the quantificationally predicting sandstone reservoir fluid saturation by combining well and seism based on the volume of voids modulus according to claim 1, the described shear wave velocity curve of step 3) utilizes Xu-White Model Calculation shear wave velocity curve when not gathering the well of shear wave slowness curve.
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