CN105447584A - Method for acquiring future explored oil gas reserves distribution of exploration target set - Google Patents
Method for acquiring future explored oil gas reserves distribution of exploration target set Download PDFInfo
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Abstract
The invention discloses a method for acquiring the future explored oil gas reserves distribution of an exploration target set. The method comprises a step 1 of: constructing a first desired distribution of an exploration target success number and a first desired distribution of an explored oil gas reserves; a step 2 of acquiring a predicted value of the exploration target success number; a step 3 of establishing an incidence relation between the first desired distribution of the exploration target success number and the first desired distribution of explored oil gas reserves; a step 4 of acquiring a second desired distribution of the exploration target success number; and a step 5 of acquiring a second desired distribution of the explored oil gas reserves so as to form the future explored oil gas reserves distribution. The method not only utilizes the empirical data of historical exploration, but also introduces quantified risk analysis so as to achieve a result closer to an actual condition. Further, since the method computes and establishes the explored oil gas reserves distribution by using random sampling, the future explored oil gas reserves distribution acquired by the method is more accurate.
Description
Technical field
The present invention relates to geological exploration field, relate to a kind of method that future obtaining Target For Drilling combination bores rear oil and gas reserves distribution specifically.
Background technology
Target For Drilling combines the intersection treating Target For Drilling optimized from exploration targets warehouse in Zhi Shi oil company year or certain batch of Exploration planning.The combination of science, rational prediction Target For Drilling is following bores the basis that rear findable oil and gas reserves scale is establishment Exploration planning.In prior art approaches, count each Target For Drilling hydrocarbon resources amount summation usually, then the experience success ratio being multiplied by Target For Drilling combination will bore rear oil and gas reserves scale to the future obtaining Target For Drilling combination.Owing to not considering oily probability and the hydrocarbon resources amount distributional difference thereof of each Target For Drilling, the Target For Drilling therefore utilizing art methods to get combination future bore after oil and gas reserves scale and actual conditions widely different, reliability is poor.
Therefore, for the problem that the reliability that predicts the outcome of oil and gas reserves scale after boring in future of Target For Drilling combination in prior art is poor, after needing bore a kind of future of acquisition Target For Drilling combination newly, the method for oil and gas reserves distribution will bore predicting the outcome of rear oil and gas reserves scale with the future obtaining the combination of more reliable Target For Drilling.
Summary of the invention
The future of the Target For Drilling combination got for utilizing prior art bores the poor problem of rear oil and gas reserves scale reliability, and the invention provides the method for oil and gas reserves distribution after boring a kind of future obtaining Target For Drilling combination, described method comprises following steps:
Step one, build described Target For Drilling combination Target For Drilling successfully several first expect distribution and described Target For Drilling combination brill after oil and gas reserves first expect distribution;
Step 2, the Target For Drilling obtaining the combination of described Target For Drilling successfully counts predicted value;
Step 3, set up described Target For Drilling successfully several first expect distribution and described brill after oil and gas reserves first expect to distribute between incidence relation;
Step 4, based on described Target For Drilling successfully count predicted value to described Target For Drilling successfully several first expect distribution screen, thus obtain Target For Drilling successfully several second expect distribution;
Step 5, based on described incidence relation obtain with described Target For Drilling successfully the several second oil and gas reserves second after corresponding brill of expecting distribute expects distribute, thus to distribute according to the rear oil and gas reserves of the described following brill of formation of expecting to distribute of oil and gas reserves second after described brill.
In one embodiment, in step 3, set up described Target For Drilling successfully several first expect in distribution each successfully count expectation value and described brill after oil and gas reserves first expect to distribute in corresponding relation between each oil and gas reserves expectation value.
In one embodiment, in step 2, the probing success ratio empirical value based on the combination of history Target For Drilling obtains described Target For Drilling and successfully counts predicted value.
In one embodiment, described step one comprises following steps:
Obtain the oily probability of each Target For Drilling in the combination of described Target For Drilling;
The oily probability Distribution Model of described Target For Drilling combination is built according to the oily probability of described each Target For Drilling;
Random sampling is carried out to described oily probability Distribution Model, thus acquisition Target For Drilling successfully counts sampling results;
Successfully count sampling results according to described Target For Drilling and build the successfully several first expectation distribution of described Target For Drilling.
In one embodiment, in the process of oily probability Distribution Model building the combination of described Target For Drilling, 0-1 distribution is adopted to build the oily probability Distribution Model of described Target For Drilling combination, in described 0-1 distribution, 0 represents Target For Drilling will drill unsuccessfully future, and 1 represents Target For Drilling will drill successfully future.
In one embodiment, repeatedly random sampling is carried out to described oily probability Distribution Model, wherein:
Based on the accuracy requirement of boring rear oil and gas reserves distribution future that described Target For Drilling combines, the number of times of described random sampling is set;
Record the Target For Drilling successfully number of each described random sampling, thus generate described Target For Drilling and successfully count sampling results.
In one embodiment, in described random sampling procedure, if the sample value of described oily probability Distribution Model is 1, then represent that this sampling Target For Drilling is drilled successfully, Target For Drilling successfully number adds 1; If the sample value of described oily probability Distribution Model is 0, then represent that this sampling Target For Drilling is drilled unsuccessfully, Target For Drilling successfully counts constant.
In one embodiment, described step one comprises following steps:
Build the hydrocarbon resources amount distributed model of described Target For Drilling combination;
Random sampling is carried out to the hydrocarbon resources amount distributed model that described Target For Drilling combines, thus obtains stock number sampling results;
After building described brill according to described Target For Drilling combined resource amount sampling results, oil and gas reserves expects the first distribution.
In one embodiment, adopt lognormal distribution to build the hydrocarbon resources amount distributed model of described each Target For Drilling, thus build the hydrocarbon resources amount distributed model of described Target For Drilling combination according to the hydrocarbon resources amount distributed model of described each Target For Drilling.
In one embodiment, repeatedly random sampling is carried out to the hydrocarbon resources amount distributed model that described Target For Drilling combines, wherein:
Based on the accuracy requirement of boring rear oil and gas reserves distribution future that described Target For Drilling combines, the number of times of described random sampling is set;
Record the stock number sum of each Target For Drilling of each described random sampling, thus generate described Target For Drilling combined resource amount sampling results.
Compared with prior art, tool of the present invention has the following advantages:
Method of the present invention utilizes random sampling to calculate and sets up the rear oil and gas reserves distribution of brill, to replace in the past rough mean estimates, bore rear oil and gas reserves its future obtained and distribute more accurate;
Method of the present invention not only make use of the empirical data of history probing in the past, but also add the venture analysis of quantification, its result, more close to actual conditions, can provide more reliable reference frame for oily company Annual Exploration planning establishment, Portfolio Optimization.
Other features and advantages of the present invention will be set forth in the following description, and, partly become apparent from instructions, or understand by implementing the present invention.Object of the present invention and other advantages realize by step specifically noted in instructions, claims and accompanying drawing and obtain.
Accompanying drawing explanation
Accompanying drawing is used to provide a further understanding of the present invention, and forms a part for instructions, with embodiments of the invention jointly for explaining the present invention, is not construed as limiting the invention.In the accompanying drawings:
Fig. 1 is implementing procedure figure according to an embodiment of the invention;
Fig. 2 is oily probability Distribution Model figure according to an embodiment of the invention;
Fig. 3 is stock number distributed model figure according to an embodiment of the invention;
Fig. 4 is that Target For Drilling successfully several first expects distributed model figure according to an embodiment of the invention;
Fig. 5 is that after following according to an embodiment of the invention boring, reserves first expect distributed model figure;
Fig. 6 is that future will be bored rear resource distribution model figure in Target For Drilling combination according to an embodiment of the invention.
Embodiment
Describe embodiments of the present invention in detail below with reference to drawings and Examples, to the present invention, how application technology means solve technical matters whereby, and the implementation procedure reaching technique effect can fully understand and implement according to this.It should be noted that, only otherwise form conflict, each embodiment in the present invention and each feature in each embodiment can be combined with each other, and the technical scheme formed is all within protection scope of the present invention.
The present invention distributes with each Target For Drilling oily probability, oil and gas reserves and Target For Drilling combination experience success ratio is data basis, use for reference exploration risk and analyze thought, utilize Monte Carlo stochastic simulation technology, generate the rear oil and gas reserves distribution of the following brill of Target For Drilling combination.Relative to previous methods, the present invention has fully taken into account exploration risk and the stock number distribution situation of each Target For Drilling, and utilize Target For Drilling combination experience success ratio to carry out achievement correction, and the form of oil and gas reserves distribution instead of in the past rough mean estimates after boring so that Target For Drilling combination is following, result of calculation more science, reliable, and embodying the venture analysis thought of quantification, its result can be the establishment of oily company Annual Exploration planning, Portfolio Optimization provides important reference.
One embodiment of the invention specific implementation flow process as shown in Figure 1.Can perform in the computer system of such as one group of computer executable instructions in the step shown in the process flow diagram of accompanying drawing, and, although show logical order in flow charts, in some cases, can be different from the step shown or described by order execution herein.
First perform step S101, build the oily probability Distribution Model of Target For Drilling combination.In the process building distributed model, consider the exploration risk of each Target For Drilling, invention introduces venture analysis.First by obtaining the oily probability of each Target For Drilling to the venture analysis of Target For Drilling.Then, based on the oily probability of each Target For Drilling, 0-1 distribution is adopted to build each Target For Drilling oily probability Distribution Model.In 0-1 distribution, 0 represents Target For Drilling will drill unsuccessfully future, and 1 represents Target For Drilling will drill successfully future, and both probability assignment are respectively the not oily probability of corresponding Target For Drilling and the oily probability of corresponding Target For Drilling.Above-mentioned steps both take into account the oily probability in Target For Drilling physical significance, take into account again probing whether this human factor of success, the oily probability Distribution Model obtained thus more close to actual conditions, more reliably.Method of the present invention, by adding the venture analysis of quantification, makes net result more close to actual conditions.
Then perform step S102, build the stock number distributed model of Target For Drilling combination.In the present embodiment, lognormal distribution is first adopted to build the hydrocarbon resources amount distributed model of each Target For Drilling in Target For Drilling combination.Then the hydrocarbon resources amount distributed model of Target For Drilling combination is built according to the hydrocarbon resources amount distributed model of each Target For Drilling.
Next just random sampling (step S110) can be done to the oily probability Distribution Model of the above-mentioned Target For Drilling combination established and hydrocarbon resources amount distributed model.In existing arbitrary sampling method, relatively more conventional is Monte Carlo method, and it is also called statistical simulation method or random sampling technology.Monte Carlo method is a kind of stochastic simulation computing method based on probability and statistical methods, is the method using random number (or more common pseudo random number) to solve a lot of computational problem.In the prior art, adopt Monte Carlo method to carry out net result that random sampling obtains is the most close to actual conditions.Therefore in the present embodiment, random sampling is carried out based on Monte Carlo method.Method of the present invention utilizes random sampling to calculate and sets up the rear oil and gas reserves distribution of brill, to replace in the past rough mean estimates, bore rear oil and gas reserves its future obtained and distribute more accurate.
Method of the present invention carries out repeatedly random sampling to distributed model.In theory, the number of times of random sampling is more, and the result finally obtained is more accurate.But due to can not be unlimited in practical operation carry out random sampling.Therefore, before doing random sampling, first to carry out step S104, the number of times of random sampling is set.In the present embodiment, bore the accuracy requirement of rear oil and gas reserves distribution the future based on Target For Drilling combination, the number of times of random sampling will be set.
Then carrying out step S103, generating random number respectively for needing two distributed models carrying out random sampling.Just can perform step S110 afterwards, carry out random sampling based on above-mentioned random number.Next the random sampling procedure of two distributed models is described respectively.
(1) for the oily probability Distribution Model of Target For Drilling combination
In each random sampling procedure, perform step S121, the Target For Drilling successfully number of each sampling of record.In the present embodiment, the Target For Drilling successfully number of each sampling is recorded by the statistical variable built for recording Target For Drilling success number.If certain Target For Drilling oily probability model sample value is 1, represent that this sampling Target For Drilling is drilled successfully, Target For Drilling successfully number adds 1; If certain Target For Drilling oily probability model sample value is 0, then represent that this sampling Target For Drilling is drilled unsuccessfully, Target For Drilling successfully counts constant.
(2) for the stock number distributed model of Target For Drilling combination
In each random sampling procedure, perform step S122, record each Target For Drilling hydrocarbon resources amount sum.Similar step S111, in the present embodiment, records each Target For Drilling stock number sum of each sampling by building statistical variable.
In the present embodiment, after each random sampling completes, need to perform step S130, judge whether random sampling number of times reaches settings.If random sampling number of times does not reach settings, then return and re-start step S103, respectively new random number is generated to two distributed models.Then utilize new random number to perform step S110, carry out new random sampling once to two distributed models respectively, and perform step S121 and step S122, the Target For Drilling recording new random sampling successfully counts and each Target For Drilling stock number sum.So be cycled to repeat execution, until random sampling number of times reaches settings.
When random sampling number of times reaches settings time, the random sampling step of distributed model is terminated thereupon.Now obtain Target For Drilling and successfully count sampling results and Target For Drilling combined resource amount sampling results.Next utilize sampling results to build and expect distribution.First carry out step S141, successfully count sampling results according to Target For Drilling and build Target For Drilling successfully several first expectation distribution.Meanwhile carry out step S142, build according to Target For Drilling combined resource amount sampling results and bore rear oil and gas reserves first expectation distribution.
Next step S150 is carried out, after setting up Target For Drilling combination drill oil and gas reserves first expect distribution and Target For Drilling successfully several first expects distribute between incidence relation, namely set up Target For Drilling successfully several first expect in each successfully count expectation value and the rear oil and gas reserves of brill expect first distribute in corresponding relation between each oil and gas reserves expectation value.
Statistics after Target For Drilling combination drill, often there is some difference for the mathematical expectation of the Target For Drilling obtained by the probability calculation of each Target For Drilling oily success number and actual results of drilling.But from oily company Annual Exploration planning angle, the probing success ratio of its Target For Drilling combination over the years is comparatively stable.Therefore, next the present embodiment carries out step S160, and the Target For Drilling obtaining Target For Drilling combination successfully counts predicted value.In this step, the probing success ratio empirical value based on the combination of history Target For Drilling corrects the Target For Drilling sum contained by the combination of current Target For Drilling, thus obtains Target For Drilling and successfully count predicted value.Method of the present invention not only adds the venture analysis of quantification, but also make use of the empirical data of history probing in the past, its result, more close to actual conditions, can provide more reliable reference frame for oily company Annual Exploration planning establishment, Portfolio Optimization.
The Target For Drilling obtained based on step S160 successfully counts predicted value, carries out step S170, screening Target For Drilling successfully several first expect distribution in Target For Drilling successfully count expectation value.Successfully count predicted value screening Target For Drilling based on Target For Drilling and successfully several first expect that the Target For Drilling in distribution successfully counts expectation value, thus obtain meet Target For Drilling that Target For Drilling successfully counts predicted value successfully several second expectation distribute.
Finally carry out step S180, the future generating Target For Drilling combination bores rear oil and gas reserves distribution.Due to establish in step S150 Target For Drilling successfully several first expect in each successfully count expectation value and after boring oil and gas reserves expect first distribute in corresponding relation between each oil and gas reserves expectation value.Therefore above-mentioned corresponding relation is utilized can to expect distribution based on oil and gas reserves second after the Target For Drilling generated in step S170 successfully several second expectation distributed acquisition brill.
The implementation process of comprehensive the invention described above, is not difficult to find out, method of the present invention utilizes random sampling to calculate and sets up the rear oil and gas reserves distribution of brill, to replace in the past rough mean estimates, bore rear oil and gas reserves its future obtained and distribute more accurate.Method of the present invention not only make use of the empirical data of history probing in the past simultaneously, but also add venture analysis, embody the venture analysis thought of quantification, its result, more close to actual conditions, can provide more reliable reference frame for oily company Annual Exploration planning establishment, Portfolio Optimization.
Next by one more specific embodiment the specific implementation process of the present embodiment is described.
For oil and gas reserves forecast of distribution after certain oily company Annual Target For Drilling combination drill.The total Target For Drilling 21 of this Target For Drilling combination, its mining resources amount and oily probability scenarios as shown in table 1.
Table 1
First oily probability Distribution Model and the hydrocarbon resources amount distributed model of each Target For Drilling is built.
The structure of oily probability Distribution Model is distributed as basis with 0-1, to be numbered the Target For Drilling of 1, builds its oily probability Distribution Model as shown in Figure 2.The histogram marking 0 in Fig. 2 represents the probability being numbered the Target For Drilling failure of 1, is 0.43; The histogram representative of mark 1 is numbered the successful probability of Target For Drilling of 1, is 0.57.
Build each Target For Drilling stock number distributed model afterwards respectively.Still for the Target For Drilling being numbered 1, according to the P10 value of its stock number, P50 value and P90 value, lognormal distribution is adopted to build its stock number distributed model as shown in Figure 3.In Fig. 3, horizontal ordinate is the stock number of Target For Drilling, and ordinate is the accumulation probability of respective resources amount.
Oily probability Distribution Model and the hydrocarbon resources amount distributed model of Target For Drillings all in shown in table 1 is built according to said method.
Target For Drilling successfully counts prediction aspect, and it is 40% that this oily company Annual Target For Drilling is combined into power empirical value, and it is 21 mouthfuls that this annual Target For Drilling combines the Target For Drilling number comprised, predict this annual Target For Drilling successfully number be 8.
According to oily probability model and the stock number distributed model of each Target For Drilling built, sample 10000 times through Monte Carlo stochastic simulation, the Target For Drilling of often being taken turns sampling by statistics is successfully counted and each Target For Drilling stock number sum, and successfully several first expectation distribution (Fig. 4) and the rear reserves first of the following brill of Target For Drilling combination expect distribution (Fig. 5) to generation Target For Drilling respectively.Set up the associations of two distributions, after recording that Target For Drilling combination is following and boring, reserves first to expect in distribution (Fig. 5) that each reserve expectation value successfully several first expects the Target For Drilling successfully number that distribution (Fig. 4) is corresponding at Target For Drilling.
Successfully count predicted value (8) according to Target For Drilling and successfully several first expect that distribution (Fig. 4) is filtered to Target For Drilling, the Target For Drilling obtaining meeting 8 Target For Drillings success numbers successfully several second expects distribution.Successfully count based on Target For Drilling and combine the following corresponding relation boring rear reserves with Target For Drilling, the combination of generation Target For Drilling is following bores rear reserves second expectation distribution, thus forms the final rear reserve distribution of the following brill of Target For Drilling combination, and net result as shown in Figure 6.
According to method of the present invention, the result finally obtained is a probability distribution.And the accordingly result that classic method obtains is one and determines unique value.Compared to classic method, the result utilizing method of the present invention to obtain is more close to actual conditions.For the instantiation in Fig. 6.In figure 6, the rear reserves of brill in future accumulating probability 90% correspondence are 1117.27 ten thousand tons, and it is 2208.03 ten thousand tons that the future of accumulation probability 10% correspondence bores rear reserves, and average (Mean) is 1614.38 ten thousand tons.The result obtained based on art methods is 1882.51 ten thousand tons.Through drilling proof after this batch of sondage objective cross, find oil workable reserve 1,512 ten thousand tons altogether, predict the outcome with the present invention and substantially meet (and than classic method closer to).
Although embodiment disclosed in this invention is as above, the embodiment that described content just adopts for the ease of understanding the present invention, and be not used to limit the present invention.The method of the invention also can have other various embodiments; when not deviating from essence of the present invention; those of ordinary skill in the art are when making various corresponding change and distortion according to the present invention, but these change accordingly and are out of shape the protection domain that all should belong to claim of the present invention.
Claims (10)
1. obtain a method of boring rear oil and gas reserves distribution future for Target For Drilling combination, it is characterized in that, described method comprises following steps:
Step one, build described Target For Drilling combination Target For Drilling successfully several first expect distribution and described Target For Drilling combination brill after oil and gas reserves first expect distribution;
Step 2, the Target For Drilling obtaining the combination of described Target For Drilling successfully counts predicted value;
Step 3, set up described Target For Drilling successfully several first expect distribution and described brill after oil and gas reserves first expect to distribute between incidence relation;
Step 4, based on described Target For Drilling successfully count predicted value to described Target For Drilling successfully several first expect distribution screen, thus obtain Target For Drilling successfully several second expect distribution;
Step 5, based on described incidence relation obtain with described Target For Drilling successfully the several second oil and gas reserves second after corresponding brill of expecting distribute expects distribute, thus to distribute according to the rear oil and gas reserves of the described following brill of formation of expecting to distribute of oil and gas reserves second after described brill.
2. the method for claim 1, it is characterized in that, in step 3, set up described Target For Drilling successfully several first expect in distribution each successfully count expectation value and described brill after oil and gas reserves first expect to distribute in corresponding relation between each oil and gas reserves expectation value.
3. the method for claim 1, is characterized in that, in step 2, the probing success ratio empirical value based on the combination of history Target For Drilling obtains described Target For Drilling and successfully counts predicted value.
4. the method for claim 1, is characterized in that, described step one comprises following steps:
Obtain the oily probability of each Target For Drilling in the combination of described Target For Drilling;
The oily probability Distribution Model of described Target For Drilling combination is built according to the oily probability of described each Target For Drilling;
Random sampling is carried out to described oily probability Distribution Model, thus acquisition Target For Drilling successfully counts sampling results;
Successfully count sampling results according to described Target For Drilling and build the successfully several first expectation distribution of described Target For Drilling.
5. method as claimed in claim 4, it is characterized in that, in the process of oily probability Distribution Model building the combination of described Target For Drilling, 0-1 distribution is adopted to build the oily probability Distribution Model of described Target For Drilling combination, in described 0-1 distribution, 0 represents Target For Drilling will drill unsuccessfully future, and 1 represents Target For Drilling will drill successfully future.
6. method as claimed in claim 5, is characterized in that, carry out repeatedly random sampling to described oily probability Distribution Model, wherein:
Based on the accuracy requirement of boring rear oil and gas reserves distribution future that described Target For Drilling combines, the number of times of described random sampling is set;
Record the Target For Drilling successfully number of each described random sampling, thus generate described Target For Drilling and successfully count sampling results.
7. method as claimed in claim 6, is characterized in that, in described random sampling procedure, if the sample value of described oily probability Distribution Model is 1, then represent that this sampling Target For Drilling is drilled successfully, Target For Drilling successfully number adds 1; If the sample value of described oily probability Distribution Model is 0, then represent that this sampling Target For Drilling is drilled unsuccessfully, Target For Drilling successfully counts constant.
8. the method for claim 1, is characterized in that, described step one comprises following steps:
Build the hydrocarbon resources amount distributed model of described Target For Drilling combination;
Random sampling is carried out to the hydrocarbon resources amount distributed model that described Target For Drilling combines, thus obtains stock number sampling results;
After building described brill according to described Target For Drilling combined resource amount sampling results, oil and gas reserves expects the first distribution.
9. method as claimed in claim 8, it is characterized in that, adopt lognormal distribution to build the hydrocarbon resources amount distributed model of described each Target For Drilling, thus build the hydrocarbon resources amount distributed model of described Target For Drilling combination according to the hydrocarbon resources amount distributed model of described each Target For Drilling.
10. method as claimed in claim 8, is characterized in that, carry out repeatedly random sampling to the hydrocarbon resources amount distributed model that described Target For Drilling combines, wherein:
Based on the accuracy requirement of boring rear oil and gas reserves distribution future that described Target For Drilling combines, the number of times of described random sampling is set;
Record the stock number sum of each Target For Drilling of each described random sampling, thus generate described Target For Drilling combined resource amount sampling results.
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