CN107356966B - Deep river sand body oil gas detection method based on de-compaction effect - Google Patents
Deep river sand body oil gas detection method based on de-compaction effect Download PDFInfo
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Abstract
The invention provides an oil-gas detection method of deep riverway sand bodies based on de-compaction, which comprises the steps of ① well logging curve editing and correction, ② acoustic wave time difference of a quasi-mudstone stratum and a sandstone stratum from shallow to deep is obtained, normal compaction trend lines of the mudstone and the sandstone are respectively established, ③ the compaction trend is subtracted from a speed curve on the well, so that a well speed curve with the de-compaction trend removed is obtained, ④ parameters such as longitudinal wave impedance, transverse wave impedance and Poisson ratio based on de-compaction are calculated, further inverse proportion Poisson ratio parameters are calculated, a threshold value of oil-gas containing exploration of a reservoir is determined through intersection analysis, ⑤ is used for carrying out pre-stack simultaneous inversion based on a Zoeppritz equation, a plurality of elastic parameter bodies are obtained, further inverse proportion Poisson ratio parameter bodies are calculated, and oil-gas containing performance of the reservoir is predicted.
Description
Technical Field
The invention relates to the field of oil-gas comprehensive exploration, in particular to an oil-gas detection method for deep river sand bodies by obtaining inverse proportion Poisson's ratio parameter bodies through prestack simultaneous inversion of a Zoeppritz equation based on the de-compaction effect.
Background
In the exploration process of oil and gas reservoirs, the oil and gas detection by utilizing seismic data plays an increasingly important role. The applications of the method are very wide from using post-stack seismic data to carry out oil-gas detection on seismic attributes, frequency division absorption attributes, bright spot technologies and the like to using pre-stack data to carry out AVO attribute analysis, Poisson impedance, pre-stack inversion and the like, and certain effects are achieved. However, for deep river sand, the degree of compaction of the sand-shale stratum is increased along with the increase of the burial depth, and the difference of the sand-shale speed is gradually reduced, so that the oil-gas sensitive attribute and the sensitive parameters are not sensitive any more, and the oil-gas detection effect is greatly reduced. Meanwhile, the research on the oil-gas detection method based on the de-compaction action for the deep reservoir is relatively less.
The compaction is a physical-chemical action in the early stage of diagenesis, and refers to the action of water discharge, porosity reduction and volume reduction under the heavy load of a water layer and a settled layer on a sediment after the sediment is settled or under the action of structural deformation.
As for the physical properties of the reservoir, a large number of researches show that in a sandstone reservoir, the compaction action is one of the main reasons for greatly reducing the primary pores in the sand body, the primary inter-particle pores in the sand body are greatly reduced due to the existence of the compaction action, and the compaction and pore reduction rate in some places can reach more than 50 percent, so that the physical properties of the reservoir of the sand body are greatly influenced.
With regard to the physical parameter difference of the sand shale rock, the compaction effect is different for different lithologies, the dependence of the well-separated compact sandstone on the depth is smaller, and the dependence of the mudstone and the poorly-separated sandstone on the depth is larger, namely: the compaction has little effect on tight sandstone and relatively great effect on mudstone and sandstone with poor separation. As the depth of burial increases, the speed difference between the sand and the mudstone is gradually reduced along with the continuous enhancement of the compaction action.
For deep river channel sand bodies, as the burial depth is large, sand mudstones in the stratum are all subjected to a strong compaction effect, so that the speed difference between the sand mudstone and the sand mudstone is gradually reduced while the porosity of the sand mudstone is rapidly reduced, and further the existing rock physical parameters cannot effectively distinguish the sand mudstones under the background of large burial depth and strong compaction, so that the problem of oil-gas detection of the river channel sand cannot be effectively solved, and the exploration and deployment of a research area are greatly influenced.
Disclosure of Invention
The invention aims to provide a prestack oil gas detection method based on compaction removal for deep channel sand bodies, which eliminates the influence of stratum compaction and improves the parameter sensitivity of reservoir fluid; meanwhile, the method breaks through the limit of various oil gas detection methods on deep river channel sand body oil gas detection, and greatly improves the prediction precision of reservoir fluid.
The deep river sand body oil gas detection method based on the de-compaction effect adopts the following steps:
(1) editing and correcting a sound wave curve;
(2) selecting the formation speed of sandstone and mudstone, and establishing a normal compaction trend line;
(3) removing the compaction trend to obtain a well speed curve after compaction removal;
(4) calculating parameters of longitudinal wave impedance, transverse wave impedance, density and Poisson ratio after compaction is removed; further calculating an inverse proportion Poisson ratio parameter on the basis, and determining a threshold value of the oil-gas content in the reservoir through intersection analysis;
(5) and performing prestack simultaneous inversion based on a Zoeppritz equation to obtain a plurality of elastic parameter bodies of longitudinal wave velocity, transverse wave velocity, density and Poisson ratio, obtaining an inverse proportion Poisson ratio parameter body through body calculation, and predicting the oil-gas content of the reservoir.
Furthermore, the fidelity of a logging curve is reduced due to factors such as well diameter, mud invasion and mud cake thickness in a logging environment, and the properties of stratum and pore fluid cannot be reflected really, so that the later reservoir prediction and oil-gas detection are seriously influenced. Therefore, the step (1) means: carrying out rock physical model-based correction aiming at the whole well section, so that abnormal points are reset, and abnormal values caused by the influence of environmental factors are eliminated;
the steps of editing and correcting the acoustic wave curve are as follows: firstly, establishing a petrophysical model of a research area according to rock frameworks and fluid characteristics; then according to the rock physical model and the physical property parameters of the normal well section, calculating the reference line of the longitudinal wave velocity of the pure sandstone and the pure mudstone along with the change of the density, using the reference line as a template, searching abnormal points, and projecting the abnormal points on the longitudinal wave velocity curve; and fitting a Faust formula by using deep direction finding well logging information which is not influenced by the change of the well diameter, and carrying out rock physical well logging correction on the well section developed at the abnormal point.
The environmental factors in the step (1) comprise factors of well diameter, mud invasion and mud cake thickness in a logging environment; the rock skeleton and fluid characteristics comprise mineral components, granularity and cement of rock; the depth measurements unaffected by the change in borehole diameter include resistivity.
Further, the specific steps of the step (2) are as follows: the method comprises the steps of firstly distinguishing mudstone and sandstone strata according to a natural gamma curve and a natural potential curve, then selecting an average value of each mudstone layer and each sandstone layer from shallow to deep on a corrected acoustic curve, and respectively establishing normal compaction curves of the sandstone strata and the mudstone strata.
The sandstone formation in the step (2) has a sandstone content of more than 90% and a porosity of less than 1%.
Further, the step (3) is to subtract the compaction trend from the corrected well speed curve to obtain a de-compacted well speed curve, and the specific steps are as follows: the method comprises the steps of firstly distinguishing sandstone and mudstone intervals from a well, and then subtracting the normal compaction trends of the sandstone and the mudstone from the lithologic intervals respectively to obtain a debulked well speed curve.
Further, because the poisson ratio is difficult to effectively distinguish an oil layer from a non-oil layer, the inverse poisson ratio in the step (4) is a new parameter which is constructed by reconstructing and transforming the poisson ratio according to the petrophysical relationship between elastic parameters, and the calculation formula is as follows:
the inverse poisson ratio is 1-1/(2 σ -1).
Firstly, according to the relationship among the longitudinal wave velocity, the transverse wave velocity, the density, the Poisson ratio and the Lame coefficient, calculating the longitudinal wave impedance, the transverse wave impedance and the Poisson ratio, and then further solving the inverse proportion Poisson ratio, wherein the specific formula is as follows:
γ＝(Vp/Vs)2
wherein Vp and Vs are longitudinal wave velocity and transverse wave velocity; rho is density; lambda and mu are respectively a first Lami constant and a second Lami constant; σ is the Poisson's ratio and γ is the proportionality coefficient.
Further, in the step (5), performing prestack simultaneous inversion based on the Zoeppritz equation to obtain a plurality of elastic parameter bodies such as longitudinal wave velocity, transverse wave velocity, density and poisson ratio, and further calculating an inverse poisson ratio parameter body to predict the oil-gas content of the reservoir.
According to the Zoeppritz equation, see the following formula,
under non-normal incidence conditions, seismic reflection is related to compressional velocity, shear velocity, and density of the earth formation, and the approximation formula of the Zoeppritz equation can be expressed as a function of poisson's ratio (σ):
therefore, by using the pre-stack seismic data and adopting the pre-stack inversion technology, a plurality of elastic parameter bodies such as longitudinal wave velocity, transverse wave velocity, density, Poisson's ratio and the like are obtained, and then inverse proportion Poisson's ratio parameters are calculated.
The inversion method comprises the following specific steps: (1) and optimizing the prestack gather. Aiming at the problems of strong random noise and low resolution of the prestack gather, the processing technologies of zero-phase deconvolution, parabolic radon transform, prestack RNA and the like of the prestack gather are utilized to carry out amplitude preservation and dryness removal processing on the prestack gather so as to improve the resolution; (2) and carrying out transverse wave estimation by using a rock physical model method. The traditional pore aspect ratio iterative algorithm is improved, a rock physical model is established by utilizing the observation result constraint under the core lamella mirror, and the estimation precision of transverse waves is greatly improved; (3) and stacking the sub-angle data, and carrying out seismic geological calibration. On the premise of ensuring that each part has higher covering times and signal-to-noise ratio, partially stacking the pre-stack gather according to an incident angle or offset, generally dividing the pre-stack gather into 3-5 partially stacked data bodies, and respectively performing seismic geological calibration on the three data bodies; (4) establishing an initial constraint model, finely adjusting various quality control parameters in the pre-stack simultaneous inversion process, finally performing inversion to obtain numerical bodies such as longitudinal wave impedance, transverse wave impedance, density, longitudinal and transverse wave velocity ratio and the like, and then calculating an inverse proportion Poisson ratio data body by using the elastic parameter bodies. (5) And (5) expanding the oil-gas containing prediction of the sand body. The method for predicting the oil-gas content of the river channel sand body based on the de-compacted prestack inverse proportion Poisson's ratio mainly comprises the following aspects: (1) the influence of stratum compaction is eliminated, and the parameter sensitivity of reservoir fluid is improved; (2) the applicability of the deep riverway sand body oil gas detection method is expanded, and the reservoir fluid prediction precision is improved.
The invention provides a method for de-compacting deep reservoir stratum, which is used for determining the influence of de-compacting treatment on the physical parameters of sand, mud and rock and developing the technical attack of deep river sand body oil gas detection on the basis of de-compacting treatment, thereby improving the accuracy of technical application.
Drawings
FIG. 1 is a flow chart of the deep river sand body oil and gas detection method based on de-compaction.
Fig. 2 is a normal compaction trend line of D2 well north three-dimensional ancient group, headtun river group sandstone and mudstone in the present case, wherein the abscissa axis is longitudinal wave time difference in unit us/m, and the ordinate axis is well depth in unit m.
FIG. 3 is a comparison of the velocity profiles before and after de-compaction of the D701 well in this case, where the log is the compressional velocity profile.
Fig. 4 is an analysis diagram of the intersection of the inverse proportion poisson ratio and natural gamma of the oil layer and the non-oil layer of the three-dimensional artesian head tun river group of the north well of D2 in the present case, wherein the abscissa axis is the inverse proportion poisson ratio, and the ordinate axis is the natural gamma.
Fig. 5 is a predicted profile of an oil reservoir from D7 well-D701 well-D702 well in this case.
Fig. 6 is a property diagram of inverse proportion poisson ratio of sand at the bottom of the three-dimensional ancient-looking group of the north well D2 in the present case.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the examples of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flow chart of the deep river sand body oil and gas detection method based on de-compaction, as shown in fig. 1, the method includes the following steps:
first, well log editing and correction.
In this case, taking a D701 well as an example, the density of the pure sandstone of the three-dimensional ancient group and the Tunghe group in the North D2 well is measured to be 2.65g/cm through laboratory measurement and analysis and test data of rock core and rock debris3The bulk modulus is 36.6, the elastic modulus is 96.6, the shear modulus is 45, and the density of pure mudstone is 2.35g/cm3The bulk modulus was 11.4, the elastic modulus was 15.4, and the shear modulus was 3. Thus, a skeleton model is established, and Ra is constructedThe ymer rock model; then according to the rock physical model and the physical property parameters of the normal well section, calculating the reference line of the velocity of the longitudinal wave of the pure sandstone and the pure mudstone along with the change of the density, taking the reference line as a template, searching abnormal points and projecting the abnormal points on a logging curve; and fitting a Faust formula by using the resistivity and other deep direction-finding well logging information which is not influenced by the change of the borehole diameter, and carrying out rock physical well logging correction on the well section developed at the abnormal point.
And secondly, selecting the formation speed of the sandstone and the mudstone, and establishing a normal compaction trend line.
In the case, a D701 well is taken as an example, a logging lithology explanation is referred, mudstone and a sandstone stratum are selected according to a natural Gamma (GR) and a natural potential curve (SP), wherein sandstone sections participating in the establishment of the sandstone stratum compaction trend need to meet the requirements (the sandstone content is greater than 90% and the porosity is less than 1%), the acoustic time difference of the sandstone and the mudstone is sequentially subjected to value taking from the buried depth of 3000m to 5000m, the average characteristic value of the curve is taken during the value taking, and a sharp peak value and a cycle skip value cannot be taken.
Fig. 2 is a normal compaction trend line of a sandstone formation and a mudstone formation, and it can be seen from the graph that the slope of the normal compaction trend line of the sandstone formation and the slope of the normal compaction trend line of the mudstone formation are not much different, which indicates that two lithologies are in the same pressure system, and the intercept is different, indicating that the two lithologies are different in compaction degree.
And thirdly, removing the compaction trend to obtain a well speed curve after compaction removal.
And aiming at the normal compaction trend of the sand and the mudstone obtained in the second step, the sandstone and the mudstone sections are still divided, low-frequency information (10Hz) of a normal compaction curve and high-frequency information (60Hz) of an actually-measured longitudinal wave time difference curve of the sand and the mudstone are selected to respectively carry out curve reconstruction, the reconstructed longitudinal wave time difference curves of the sandstone and the mudstone are spliced, the longitudinal wave time difference curve of the well after the compaction trend is removed is finally obtained, and the well speed curve after the compaction trend is removed is obtained through conversion of the relationship between the longitudinal wave time difference and the speed.
FIG. 3 is a well velocity curve before and after the D701 well de-compaction trend, from which it can be seen that the difference in sandstone-shale velocity is significantly increased after de-compaction.
And fourthly, calculating parameters such as longitudinal wave impedance, transverse wave impedance, density, Poisson ratio and the like after compaction, further calculating inverse proportion Poisson ratio parameters on the basis, and determining the threshold value of the oil gas in the reservoir through intersection analysis.
According to the relationship among the longitudinal wave velocity, the transverse wave velocity, the density, the Poisson ratio and the Lame coefficient, calculating the longitudinal wave impedance, the transverse wave impedance and the Poisson ratio, and then further solving the inverse proportion Poisson ratio, wherein the specific formula is as follows:
γ＝(Vp/Vs)2
inverse ratio Poisson's ratio 1-1/(2 sigma-1)
Wherein Vp and Vs are longitudinal wave velocity and transverse wave velocity; rho is density; lambda and mu are respectively a first Lami constant and a second Lami constant; σ is the Poisson's ratio and γ is the proportionality coefficient.
Fig. 4D2 is a cross analysis diagram of inverse proportion poisson's ratio of oil layers and non-oil layers of a three-dimensional northern collichmic group and a cycloarth group and natural gamma, which confirms that the inverse proportion poisson's ratio can better distinguish reservoir oil-gas content, and determines that the inverse proportion poisson's ratio 2.9 is a threshold value for determining whether the reservoir contains oil or not.
And fifthly, performing prestack simultaneous inversion based on the Zoeppritz equation, calculating an inverse proportion Poisson ratio parameter body, and predicting the oil-gas content of the reservoir.
The pre-stack inversion based on the Zoeppritz equation is carried out on the three-dimensional Qigu group and the Tutun river group in the D2 well in the case, firstly, on the premise of ensuring that each part has higher covering times and signal-to-noise ratio, the three-dimensional pre-stack channel set in the D2 North of the quanzhong is divided into 3 partially-stacked data volumes (respectively 5-15 degrees, 15-25 degrees and 25-35 degrees) according to the incident angle. And then, respectively carrying out seismic and geological calibration on the three data volumes, extracting wavelets and establishing a uniform time-depth relation. And establishing an initial constraint model, finely adjusting various quality control parameters in the pre-stack simultaneous inversion process, and finally performing inversion to obtain data bodies such as longitudinal wave impedance, transverse wave impedance, density, longitudinal and transverse wave velocity ratio and the like. And calculating an inverse proportion Poisson ratio data body by using the relationship between the inverse proportion Poisson ratio in the last step and parameters such as longitudinal wave impedance and transverse wave impedance, and developing the oil-gas prediction of the reservoir.
Fig. 5 is a predicted profile of an oil reservoir from D7 well-D701 well-D702 well. From the inversion result of the prestack inverse proportion poisson ratio, only the oil layer at the bottom of the D701 well Zenggu group presents the characteristic of low inverse proportion poisson ratio, the target layers of the D7 well and the D702 well integrally present the characteristic of the inverse proportion poisson ratio higher than that of the oil layer of the D701 well, the actual drilling result is that only the sand body of the D701 well obtains industrial oil flow, and the inversion result of the prestack inverse proportion poisson ratio is completely consistent with the effective reservoir distribution result obtained by drilling.
Further extracting the inverse proportion poisson ratio parameter attribute of the sand body at the bottom of the ancient-style group, obtaining the inverse proportion poisson ratio plane attribute of the sand body, and finally obtaining the effective reservoir plane distribution at the bottom of the ancient-style group according to the low inverse proportion poisson ratio characteristic of oil and gas, as shown in fig. 6. From the prediction results, in addition to sand bodies of industrial oil flow obtained from the D701 well, a plurality of effective reservoir development areas with larger areas are present, and the area is 35.2km2This result provides a favorable geophysical basis for further exploration of the three-dimensional north of the quasi-central region D2.
The above-mentioned embodiments are further illustrative of the objects, technical solutions and advantages of the present invention, and it should be understood that the above-mentioned embodiments are only illustrative of the present invention and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (3)
1. The deep river sand body oil gas detection method based on the de-compaction effect is characterized by comprising the following steps of:
(1) editing and correcting a sound wave curve;
(2) selecting the formation speed of sandstone and mudstone, and establishing a normal compaction trend line;
(3) removing the compaction trend to obtain a well speed curve after compaction removal;
(4) calculating parameters of longitudinal wave impedance, transverse wave impedance, density and Poisson ratio after compaction is removed; further calculating an inverse proportion Poisson ratio parameter on the basis, and determining a threshold value of the oil-gas content in the reservoir through intersection analysis;
(5) carrying out prestack simultaneous inversion based on a Zoeppritz equation to obtain a plurality of elastic parameter bodies of longitudinal wave velocity, transverse wave velocity, density and Poisson ratio, further calculating an inverse Poisson ratio parameter body, and predicting the oil-gas content of a reservoir stratum;
the step (1) is as follows: carrying out rock physical model-based correction aiming at the whole well section, so that abnormal points are reset, and abnormal values caused by the influence of environmental factors are eliminated;
the steps of editing and correcting the acoustic wave curve are as follows: firstly, establishing a petrophysical model of a research area according to rock frameworks and fluid characteristics; then according to the rock physical model and the physical property parameters of the normal well section, calculating the reference line of the longitudinal wave velocity of the pure sandstone and the pure mudstone along with the change of the density, using the reference line as a template, searching abnormal points, and projecting the abnormal points on the longitudinal wave velocity curve; fitting a Faust formula by using deep direction finding well logging information which is not influenced by the change of the well diameter, and carrying out rock physical well logging correction on the well section developed at the abnormal point;
the specific steps of the step (2) are as follows: firstly, distinguishing mudstone and sandstone strata according to a natural gamma curve and a natural potential curve, then selecting the average value of each mudstone layer and the sandstone layer from shallow to deep on the corrected acoustic curve, and respectively establishing normal compaction curves of the sandstone strata and the mudstone strata;
the specific steps of the step (3) are as follows: firstly, distinguishing sandstone and mudstone intervals from a well, and then respectively subtracting the normal compaction trends of the sandstone and the mudstone from the lithologic intervals to obtain a debulked well speed curve;
the inverse proportion Poisson's ratio in the step (4) is a new parameter constructed by reconstructing and transforming the Poisson's ratio according to the petrophysical relationship among the elastic parameters, and the calculation formula is as follows:
inverse ratio poisson ratio =1-1/(2 σ -1);
in the step (5), the developing of the prestack simultaneous inversion based on the Zoeppritz equation is performed because an approximate formula of the Zoeppritz equation can be expressed as a function of the poisson ratio (σ), and the formula is as follows:
the prestack inversion is carried out by utilizing the prestack seismic data, a plurality of elastic parameter bodies of longitudinal wave velocity, transverse wave velocity, density and Poisson ratio can be obtained, and then inverse proportion Poisson ratio parameters are calculated;
the method for predicting the oil-gas content of the river channel sand body based on the de-compacted prestack inverse proportion Poisson's ratio mainly comprises the following aspects: (1) the influence of stratum compaction is eliminated, and the parameter sensitivity of reservoir fluid is improved; (2) the applicability of the deep riverway sand body oil gas detection method is expanded, and the reservoir fluid prediction precision is improved.
2. The deep riverway sand body oil and gas detection method based on the de-compaction effect according to claim 1, characterized in that: the environmental factors in the step (1) comprise factors of well diameter, mud invasion and mud cake thickness in a logging environment; the rock skeleton and fluid characteristics comprise mineral components, granularity and cement of rock; the depth measurements unaffected by the change in borehole diameter include resistivity.
3. The deep riverway sand body oil and gas detection method based on the de-compaction effect according to claim 1, characterized in that: the sandstone formation in the step (2) has a sandstone content of more than 90% and a porosity of less than 1%.
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