CN111580180B - Ancient underground river reservoir model optimization method based on target - Google Patents
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Abstract
The invention relates to a target-based ancient underground river reservoir model optimization method, relates to the technical field of carbonate reservoir development geology, and is used for solving the technical problem that an ancient underground river reservoir model obtained by a single-attribute truncation method in the prior art is discontinuous. According to the method for optimizing the model of the ancient underground river reservoir based on the target, the initial model of the three-dimensional space distribution of the ancient underground river reservoir is optimized according to the combination of static data and dynamic data, so that the connectivity of the dynamic data is consistent with the continuity of the static data, and the three-dimensional geological model which is continuously distributed in space is obtained and accords with geological rules and dynamic characteristics.
Description
Technical Field
The invention relates to the technical field of carbonate reservoir development geology, in particular to a target-based ancient underground river reservoir model optimization method.
Background
The ancient underground river is an important reservoir type of a fracture-cave oil reservoir and is a main contributor to the oil field yield of the Tahe. The three-dimensional geological model is the key of geological research in oil field development.
The early modeling method for the ancient underground river reservoir body is mainly developed by taking a karst cave as a whole, and the method is mainly to cut off by using seismic attributes capable of reflecting characteristics of the karst cave. The method can reflect the spatial distribution characteristics of isolated karst caves to a certain extent. But there is a big problem for the ancient underground river reservoir because the ancient underground river is a near-striped reservoir with better continuity. The discontinuity of the ancient and underground river reservoir body model obtained by the single-attribute truncation method has great influence on subsequent numerical simulation and development scheme adjustment.
The existing construction method for ancient underground rivers is for example the Chinese patent CN106640027A, it discloses a construction method of a spatial structure well pattern of a cave type oil reservoir underground river type karst reservoir body, in particular to a well pattern deployment principle determined by the development characteristics and the communication mode of the underground river type karst reservoir body, then determining an injection and production well according to the production condition of the well, the type and the space position of the reservoir encountered by drilling and the communication condition among wells, thereby ensuring the optimal configuration of the water injection well, the oil production well and the reservoir body on the space structure, effectively improving the effectiveness of injection and production design, the degree of water drive and the water injection development effect, but it does not disclose how to build the model of the ancient underground river reservoir body and how to overcome the shortcoming of discontinuity of the model of the ancient underground river reservoir body in the prior art, therefore, how to establish a continuous model of the ancient underground river reservoir is an urgent problem to be solved in the current research work.
Disclosure of Invention
The invention provides a target-based ancient underground river reservoir body model optimization method, which is used for solving the technical problem of discontinuity of an ancient underground river reservoir body model obtained by a single-attribute truncation method in the prior art.
The invention provides a target-based ancient underground river reservoir model optimization method, which comprises the following operation steps of:
step S10: obtaining an initial model of three-dimensional space distribution of the ancient underground river reservoir body according to the static data of the research area;
step S20: and optimizing the initial model by adopting a target-based simulation method according to the dynamic data of the research area to obtain a continuous three-dimensional geological model of the ancient and underground river reservoir body.
In one embodiment, the continuous ancient-underground river reservoir three-dimensional geological model has similar statistical regularity with the discontinuous initial model.
In one embodiment, step S20 includes the following sub-steps:
step S21: determining a discontinuous initial model among the initial models;
step S22: determining the type of the communication channel of the research area as an interwell communication channel communicated with the ancient underground river according to the dynamic data;
step S23: and correcting the discontinuous initial model by using the statistical parameters of the real reservoir body as conditional data and using the trend line, the source point and the vertical development probability as constraint conditions by using a target-based random simulation method to obtain a continuous ancient and underground river reservoir body three-dimensional geological model with similar statistical rules.
In one embodiment, step S23 includes the following sub-steps:
step S231: determining a first source point and a second source point at the position of the river channel disconnection in the initial model;
step S232: in the initial model, determining a trend line according to the flow direction of the river channel;
step S233: dividing the river channel in the initial model into a first river channel section and a second river channel section;
the first river channel section comprises a first source point and a river channel section discontinuous from the first source point, and the second river channel section comprises a second source point and a river channel section discontinuous from the second source point;
step S234: respectively taking a first source point and a second source point as starting points, inputting statistical parameters of real reservoirs under the control of a trend line, and carrying out target-based random simulation by taking vertical development probability as a constraint condition to respectively obtain a first simulated river channel section and a second simulated river channel section;
the first simulated riverway section and the first riverway section have statistical similarity; the second simulated riverway section and the second riverway section have statistical similarity;
step S235: the intersection between the first simulated riverway section and the second simulated riverway section is an overlapped riverway section; and adding the superposed river channel section into the river channel in the initial model to obtain a continuous river channel with similar statistical rules.
In one embodiment, the static data includes seismic data volumes and geological development rules and the dynamic data includes tracer concentration curves.
In one embodiment, step S10 includes the following sub-steps:
step S11: cutting off the seismic data volume to obtain the initial distribution of the karst caves;
step S12: and identifying the ancient underground river in the initial distribution of the karst cave according to a geological development rule to obtain an initial model of the ancient underground river three-dimensional spatial distribution.
In one embodiment, the seismic data volume includes a root mean square amplitude and a wave impedance.
In one embodiment, the geological development law includes that the ancient underground river reservoirs are located at the underground water level and the ancient underground rivers are in a form of horizontal continuous distribution on the seismic attribute plane and section.
In one embodiment, the ancient underground river communication channel is determined according to the peak shape on the tracer concentration curve.
In one embodiment, the statistical parameters of the real reservoir include wavelength, amplitude, width, and thickness.
Compared with the prior art, the invention has the advantages that: according to the combination of the static data and the dynamic data, the initial model of the three-dimensional space distribution of the ancient underground river reservoir body is optimized, so that the connectivity of the dynamic data is consistent with the continuity of the static data, and the three-dimensional geological model which is continuously distributed in space is obtained and accords with the geological rule and the dynamic characteristic.
Drawings
The invention will be described in more detail hereinafter on the basis of embodiments and with reference to the accompanying drawings.
Fig. 1 is a flow chart of a method for optimizing a model of a ancient underground river reservoir in an embodiment of the invention;
FIG. 2 is an initial model diagram of the three-dimensional spatial distribution of a unit of ancient-inland river reservoir in an embodiment of the present invention;
FIGS. 3 a-3 g are process diagrams of a target-based stochastic simulation method in an embodiment of the invention;
fig. 4 is a diagram of the probability of vertical development of the ancient underground river in the embodiment of the present invention.
Detailed Description
The invention will be further explained with reference to the drawings.
As shown in fig. 1, the invention provides a target-based ancient underground river reservoir model optimization method, which optimizes an ancient underground river reservoir model based on the combination of static data and dynamic data, so as to establish a high-precision three-dimensional geological model which better meets geological reality and meets the requirement of numerical reservoir simulation and accurate calculation.
The static data comprises a seismic data body and a geological development rule, and the dynamic data comprises a tracer concentration curve. Wherein the seismic data volume includes a root mean square amplitude and a wave impedance.
In one embodiment, the method of the present invention comprises the following operational steps:
the first step is as follows: and obtaining an initial model of the three-dimensional space distribution of the ancient underground river reservoir body according to the static data of the research area.
Specifically, the initial model is obtained by multi-attribute joint truncation.
Firstly, the seismic data volume is cut off to obtain the initial distribution of the karst cave. The seismic attributes can predict the karst cave reservoirs, such as root mean square amplitude and wave impedance are two effective attributes for predicting the karst cave, and the seismic information abnormal response of the surface karst cave and the middle and deep karst cave is different. And respectively using different seismic attribute threshold values to cut off in the surface layer zone and the middle and deep layers according to the root-mean-square amplitude and the wave impedance to obtain the initial distribution of the karst cave. The two data volumes are fused to achieve the effect of mutual constraint, and the accuracy of karst cave identification can be improved.
Secondly, identifying the ancient underground river in the initial distribution of the karst cave according to a geological development rule, and obtaining an initial model of the three-dimensional spatial distribution of the ancient underground river. The geological development law comprises the states that ancient underground river reservoirs are located at underground diving surfaces and ancient underground rivers are transversely and continuously distributed on seismic attribute planes and sections.
The identification of ancient and underground rivers requires the comprehensive geological development law. The basis is as follows: firstly, the difference in depth is that the ancient underground river reservoirs are formed due to underground diving erosion, so that the ancient underground river reservoirs are mostly positioned near the underground diving surface; secondly, the ancient underground rivers are in a form of horizontal continuous distribution on seismic attribute planes and sections. On the basis of original distribution of karst caves after seismic data volume truncation, an initial model of the three-dimensional spatial distribution of the ancient and underground rivers can be obtained by endowing geological significance of the karst caves with the original distribution.
The second step is that: and optimizing the initial model by adopting a target-based simulation method according to the dynamic data of the research area to obtain a continuous three-dimensional geological model of the ancient and underground river reservoir body.
Furthermore, the obtained continuous three-dimensional geological model of the ancient and underground river reservoir body and the discontinuous initial model have similar statistical rules, so that the three-dimensional space quantitative distribution of the ancient and underground river reservoir body can be more accurately revealed, and the method has important guiding significance for efficiently developing the oil reservoir.
The method for specifically obtaining the continuous three-dimensional geological model of the ancient underground river reservoir body comprises the following steps:
firstly, determining a discontinuous initial model in the initial model, and secondly determining the type of a communication channel in a research area as an interwell communication channel communicated with the ancient underground river according to dynamic data.
It should be noted that the types of communication channels between wells include ancient underground rivers, cracks and fracture-cave complexes.
The cavern can embody distinct shapes and spreading rules under the control of different factors. Therefore, the method is independently optimized for the ancient and underground river reservoirs when being optimized, can better reflect the control effect of geological rules on the model, and avoids the interference of different types of karst caves in the simulation process.
The ancient and underground river communication channel can be determined through the peak form on the concentration curve of the tracer. Specifically, according to the single channel theory, the concentration changes with time with a peak shape. According to the peak shape, whether the communication channel belongs to the ancient underground river, the crack or the fracture-cave complex can be judged. The peak has two forms, namely a peak and a broad peak.
If the wells are communicated through the ancient underground river, the tracer is diluted and shows a broad peak on a concentration duration curve; if connected by a single crack, it appears as a spike on the concentration profile.
In addition, if the concentration duration curve is a multi-peak curve, it indicates that there are multiple ancient underground rivers or fractures between two wells, so the number of the connected channels can be analyzed according to the number of peaks.
Finally, if the ancient underground river communication is determined among wells but the ancient underground river initial model is not continuous, the initial model can be optimized by adopting a simulation method based on a target, and the prior geological knowledge can be easily added into the model as condition information by adopting a random simulation method based on the target.
Specifically, the method comprises the steps of correcting the discontinuous initial model by using statistical parameters of a real reservoir body as conditional data and using trend lines, source points and vertical development probability as constraint conditions through a target-based random simulation method to obtain a continuous ancient-underground river reservoir body three-dimensional geological model with similar statistical rules, and therefore the problem of discontinuity of the reservoir body in a modeling result is solved.
Trend lines, source points and vertical developmental probabilities are three trends based on random modeling of targets. The trend line can determine the flowing direction of the river channel, so that the river channel only develops along the trend line; the source point can determine the starting position of the river channel; the vertical development probability can ensure that the development of the result in the vertical direction after simulation is consistent with the condition data. The three components are combined to determine that the river channel grows from a specific source point along the trend line direction, and meanwhile, the vertical growth accords with the statistical probability.
In addition, the statistical parameters of the real reservoir body comprise geometric statistical parameters such as wavelength, amplitude, width and thickness, and the data can be used as conditional data input to ensure that the statistical characteristics of the final simulation result are similar to those of the original model.
The method of the present invention will be described in detail below by taking an Ordovician reservoir, which is a unit of a Tahe oil field, as an example.
Firstly, obtaining an initial model of three-dimensional space distribution of the ancient underground river reservoir body according to static data of a research area.
First, the seismic data volume is truncated. As shown in table 1, for two attributes of the root mean square amplitude and the wave impedance, in the surface layer band, if the attribute value satisfies both the condition a and the condition C, the solution cavity is defined, and if the attribute value does not satisfy the condition, the solution cavity is not considered as the solution cavity, and the abandonment processing is performed; in the middle and deep layer, if the attribute value satisfies both the condition B and the condition D, the solution cavity is defined, and the grids which do not meet the condition are not regarded as the solution cavity and are subjected to abandon processing. The two data volumes are fused to achieve the effect of mutual constraint, and the accuracy of the karst cave is improved.
Table 1 data volume type condition list
Secondly, an initial model of the ancient underground river is obtained. According to the development position of the karst caves in the unit, the karst caves are transversely and continuously distributed on the seismic attribute plane and the section at the buried depth of about 5500 meters. Accordingly, we define it as the ancient underground river reservoir and obtain an initial model of the three-dimensional spatial distribution of the ancient underground river (as shown in fig. 2).
And secondly, optimizing the initial model by adopting a target-based simulation method according to the dynamic data of the research area to obtain a continuous three-dimensional geological model of the ancient and underground river reservoir body.
As shown in table 2, the correspondence between tracer concentration curves and types of communication channels between wells is shown. The change characteristics of the tracer concentration curve in the table 2 can be used for determining the type of the inter-well communication channel inside the fractured-vuggy reservoir.
TABLE 2 Interwell communication channel type List
In the equivalent model diagram shown in table 2, the upper right point represents a producing well and the lower left point represents a water injection well.
As shown in table 3, tracer response statistics are shown, and the type of communication channel between W3 and W4 is ancient inland river communication according to table 3.
TABLE 3 Tracer response statistics List
And secondly, optimizing the initial model by adopting a random simulation method based on the target.
1. As shown in fig. 3a, there are two discontinuous channel segments in the initial model, namely, the initial channel 11 and the initial channel 21, and these two channel segments are disconnected at a. Two source points, namely the first source point 12 and the second source point 22, are respectively determined at the location of the disconnection.
2. In the initial model, a trend line 3 is determined according to the flow direction of the river, as shown in fig. 3 b.
3. And dividing the river channel in the initial model into a first river channel section 1 and a second river channel section 2. As shown in fig. 3c, the first channel segment 1 comprises a first source point 12 and a channel segment discontinuous from the first source point 1 (i.e. the initial channel 11), and the second channel segment 2 comprises a second source point 22 and a channel segment discontinuous from the second source point 22 (i.e. the initial channel 21).
4. Starting from the first source point 12 and the second source point 22, respectively, statistical parameters of the real reservoir are input under the control of the trend line 3. As shown in Table 4, the statistical parameters of the real reservoir include wavelength, amplitude, width and thickness.
TABLE 4 statistical parameter List of true reservoirs
As shown in fig. 4, random simulation based on the target is performed with the vertical development probability as the constraint condition, and a first simulated channel segment 4 and a second simulated channel segment 5 are obtained respectively (as shown in fig. 3 d).
It should be noted that the darker part in fig. 4 is another type of karst cave, and the lighter part is an ancient underground river reservoir.
The first simulated riverway section 4 and the first riverway section 1 have statistical similarity; the second simulated channel segment 5 and the second channel segment 2 have statistical similarity.
5. As shown in fig. 3e, the intersection between the first simulated riverway section 4 and the second simulated riverway section 5 is a superposed riverway section 6; as shown in fig. 3f, the overlapped river channel segment 6 is added to the river channel in the initial model to obtain a continuous river channel 7 with similar statistical rules (as shown in fig. 3 g), wherein the river channel encircled by the dotted line portion in fig. 3g is the overlapped river channel segment 6.
In conclusion, the method of the invention obtains the initial model of the three-dimensional space distribution of the ancient underground river reservoir body by utilizing a multi-seismic attribute joint truncation method; determining whether the inter-well is communicated with the ancient underground river or not according to the dynamic data; and then, taking the statistical parameters of the real reservoir body as conditional data, taking the trend line, the source point and the vertical development probability as constraints, and modifying and optimizing the initial model by adopting target-based random simulation to obtain the continuous ancient and underground river reservoir body three-dimensional geological model with similar statistical rules. Therefore, the method has a very wide application prospect in the field of carbonate fracture-cave reservoir modeling, and has important practical significance for fine description, numerical simulation and reasonable formulation of development schemes of the reservoirs.
While the invention has been described with reference to a preferred embodiment, various modifications may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In particular, the technical features mentioned in the embodiments can be combined in any way as long as there is no structural conflict. It is intended that the invention not be limited to the particular embodiments disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.
Claims (9)
1. A target-based ancient underground river reservoir model optimization method is characterized by comprising the following operation steps:
step S10: obtaining an initial model of three-dimensional space distribution of the ancient underground river reservoir body according to the static data of the research area;
step S20: optimizing the initial model by adopting a target-based simulation method according to the dynamic data of the research area to obtain a continuous three-dimensional geological model of the ancient and underground river reservoir body;
step S20 includes the following substeps:
step S21: determining a discontinuous initial model among the initial models;
step S22: determining the type of the communication channel of the research area as an interwell communication channel communicated with the ancient underground river according to the dynamic data;
step S23: and correcting the discontinuous initial model by using the statistical parameters of the real reservoir body as conditional data and using the trend line, the source point and the vertical development probability as constraint conditions by using a target-based random simulation method to obtain a continuous ancient and underground river reservoir body three-dimensional geological model with similar statistical rules.
2. The goal-based paleo-underground river reservoir model optimization method of claim 1, wherein the continuous paleo-underground river reservoir three-dimensional geological model has similar statistical regularity as the discontinuous initial model.
3. The method of target-based paleounderground river reservoir model optimization according to claim 1, wherein step S23 includes the sub-steps of:
step S231: determining a first source point and a second source point at the position of the river channel disconnection in the initial model;
step S232: in the initial model, determining a trend line according to the flow direction of the river channel;
step S233: dividing the river channel in the initial model into a first river channel section and a second river channel section;
the first river channel section comprises a first source point and a river channel section discontinuous from the first source point, and the second river channel section comprises a second source point and a river channel section discontinuous from the second source point;
step S234: respectively taking a first source point and a second source point as starting points, inputting statistical parameters of real reservoirs under the control of a trend line, and carrying out target-based random simulation by taking vertical development probability as a constraint condition to respectively obtain a first simulated river channel section and a second simulated river channel section;
the first simulated riverway section and the first riverway section have statistical similarity; the second simulated riverway section and the second riverway section have statistical similarity;
step S235: the intersection between the first simulated riverway section and the second simulated riverway section is an overlapped riverway section; and adding the superposed river channel section into the river channel in the initial model to obtain a continuous river channel with similar statistical rules.
4. The method of target-based paleounderground river reservoir model optimization according to claim 1, wherein the static data comprises seismic data volumes and geological development rules and the dynamic data comprises tracer concentration curves.
5. The method of target-based paleounderground river reservoir model optimization according to claim 4, wherein step S10 includes the sub-steps of:
step S11: cutting off the seismic data volume to obtain the initial distribution of the karst caves;
step S12: and identifying the ancient underground river in the initial distribution of the karst cave according to a geological development rule to obtain an initial model of the ancient underground river three-dimensional spatial distribution.
6. The method of target-based ancient underground river reservoir model optimization of claim 5, wherein the seismic data volume comprises root mean square amplitude and wave impedance.
7. The method of target-based paleo-underground river reservoir model optimization according to claim 6, wherein the geological development rules include paleo-underground river reservoirs located at the subsurface and paleo-underground rivers in a horizontally continuous distribution on seismic attribute planes and profiles.
8. The method of target-based paleo-dark-river reservoir model optimization of claim 4, wherein paleo-dark-river connected channels are determined according to peak morphology on the tracer concentration curve.
9. The method of target-based ancient dark river reservoir model optimization of claim 1, wherein the statistical parameters of the real reservoir include wavelength, breadth, width and thickness.
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