CN105447584B - Method for obtaining future post-drilling oil and gas reserve distribution of drilling target combination - Google Patents
Method for obtaining future post-drilling oil and gas reserve distribution of drilling target combination Download PDFInfo
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Abstract
The invention discloses a method for acquiring future post-drilling oil and gas reserves distribution of a drilling target combination, which comprises the following steps: step one, constructing a drilling target success number and a first expected distribution of oil and gas reserves after drilling; step two, obtaining a predicted value of the success number of the drilling target; establishing an incidence relation between the first expected distribution of the drilling target success number and the first expected distribution of the oil and gas reserves after drilling; step four, obtaining a second expected distribution of drilling target success numbers; and step five, acquiring a second expected distribution of the oil and gas reserves after drilling, thereby forming the future oil and gas reserve distribution after drilling. The method not only utilizes the past historical drilling experience data, but also adds quantitative risk analysis, and the result is closer to the actual situation; and because the method of the invention utilizes random sampling to calculate and establish the oil and gas reserves distribution after drilling, the acquired oil and gas reserves distribution after drilling in the future is more accurate.
Description
Technical Field
The invention relates to the field of geological exploration, in particular to a method for acquiring future post-drilling oil and gas reserve distribution of a drilling target combination.
Background
The drilling target combination refers to the aggregate of targets to be drilled which are selected from the exploration target storage library in the oil company year or a certain batch of exploration plans. Scientifically and reasonably predicting the size of the oil and gas reserves which can be found after the drilling target combination is drilled in the future is the basis for making an exploration plan. In the prior art method, the future drilled hydrocarbon reserve size of the drilling target combination is obtained by summing the calculated amount of each drilling target hydrocarbon resource and multiplying the sum by the empirical success rate of the drilling target combination. Because the oil-gas containing probability and the oil-gas resource amount distribution difference of each drilling target are not considered, the future drilled oil-gas reserve size of the drilling target combination obtained by the prior art method is greatly different from the actual situation, and the reliability is poor.
Therefore, in order to solve the problem of poor reliability of the prediction result of the future after-drilling oil and gas reserve scale of the drilling target combination in the prior art, a new method for obtaining the future after-drilling oil and gas reserve distribution of the drilling target combination is needed to obtain a more reliable prediction result of the future after-drilling oil and gas reserve scale of the drilling target combination.
Disclosure of Invention
Aiming at the problem of poor scale reliability of future post-drilling oil and gas reserves of a drilling target combination obtained by the prior art, the invention provides a method for obtaining the future post-drilling oil and gas reserves distribution of the drilling target combination, which comprises the following steps:
step one, constructing a first expected distribution of drilling target success numbers of the drilling target combination and a first expected distribution of oil and gas reserves after drilling of the drilling target combination;
step two, obtaining a drilling target success number predicted value of the drilling target combination;
establishing an incidence relation between the first expected distribution of the drilling target success number and the first expected distribution of the oil and gas reserves after drilling;
screening the first expected distribution of the drilling target success numbers based on the drilling target success number predicted value so as to obtain a second expected distribution of the drilling target success numbers;
and fifthly, acquiring a second expected distribution of the oil and gas reserves after drilling corresponding to the second expected distribution of the drilling target success number based on the incidence relation, and forming the future oil and gas reserve after drilling according to the second expected distribution of the oil and gas reserves after drilling.
In one embodiment, in step three, a corresponding relationship between each expected value of the success number in the drilling target success number first expected distribution and each expected value of the hydrocarbon reserves in the post-drilling hydrocarbon reserve first expected distribution is established.
In one embodiment, in step two, the drilling target success number predicted value is obtained based on the drilling success rate empirical value of the historical drilling target combination.
In one embodiment, the first step comprises the steps of:
acquiring the hydrocarbon-bearing probability of each drilling target in the drilling target combination;
constructing a hydrocarbon-bearing probability distribution model of the drilling target combination according to the hydrocarbon-bearing probability of each drilling target;
randomly sampling the hydrocarbon-containing probability distribution model to obtain a drilling target success number sampling result;
and constructing a first expected distribution of the drilling target success number according to the sampling result of the drilling target success number.
In one embodiment, in constructing the hydrocarbon-bearing probability distribution model of the drilling target combination, the hydrocarbon-bearing probability distribution model of the drilling target combination is constructed using a 0-1 distribution, where 0 represents a future drilling failure of the drilling target and 1 represents a future drilling success of the drilling target in the 0-1 distribution.
In one embodiment, the hydrocarbon-bearing probability distribution model is randomly sampled a plurality of times, wherein:
setting the number of times of the random sampling based on the accuracy requirement of future post-drilling hydrocarbon reserve distribution of the drilling target combination;
recording the drilling target success number of each random sampling, thereby generating the drilling target success number sampling result.
In one embodiment, in the random sampling process, if the sampling value of the hydrocarbon-containing probability distribution model is 1, it indicates that the drilling target of the sampling is successfully drilled, and the drilling target success number is increased by 1; if the sampling value of the hydrocarbon-containing probability distribution model is 0, the drilling failure of the sampling drilling target is represented, and the success number of the drilling target is unchanged.
In one embodiment, the first step comprises the steps of:
constructing a hydrocarbon resource quantity distribution model of the drilling target combination;
randomly sampling the oil and gas resource quantity distribution model of the drilling target combination so as to obtain a resource quantity sampling result;
and constructing the expected first distribution of the oil and gas reserves after drilling according to the sampling result of the drilling target combined resource amount.
In one embodiment, the hydrocarbon resource amount distribution model of each drilling target is constructed by using a lognormal distribution, so that the hydrocarbon resource amount distribution model of the drilling target combination is constructed according to the hydrocarbon resource amount distribution model of each drilling target.
In one embodiment, the hydrocarbon resource amount distribution model of the drilling target combination is randomly sampled a plurality of times, wherein:
setting the number of times of the random sampling based on the accuracy requirement of future post-drilling hydrocarbon reserve distribution of the drilling target combination;
recording the sum of the resource amount of each drilling target sampled at each time randomly, thereby generating the drilling target combined resource amount sampling result.
Compared with the prior art, the invention has the following advantages:
the method utilizes random sampling to calculate and establish the oil and gas reserves distribution after drilling so as to replace the former rough average estimated value, and the acquired oil and gas reserves distribution after drilling in the future is more accurate;
the method not only utilizes the past historical drilling experience data, but also adds quantitative risk analysis, the result is closer to the actual situation, and more reliable reference basis can be provided for annual exploration planning and investment portfolio optimization of oil companies.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the process particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is an implementation flow diagram according to an embodiment of the invention;
FIG. 2 is a graph of a hydrocarbon containing probability distribution model according to an embodiment of the invention;
FIG. 3 is a diagram of a resource amount distribution model according to an embodiment of the invention;
FIG. 4 is a diagram of a first desired distribution model of drilling target success numbers according to an embodiment of the present invention;
FIG. 5 is a model diagram of a first expected distribution of future post-drill reserves, according to an embodiment of the present invention;
FIG. 6 is a plot of a drilling target combined future post-drilling reserve distribution model according to an embodiment of the invention.
Detailed Description
The following detailed description of the embodiments of the present invention will be provided with reference to the drawings and examples, so that how to apply the technical means to solve the technical problems and achieve the technical effects can be fully understood and implemented. It should be noted that, as long as there is no conflict, the embodiments and the features of the embodiments of the present invention may be combined with each other, and the technical solutions formed are within the scope of the present invention.
The method takes the oil-gas containing probability of each drilling target, the oil-gas reserve distribution and the experience success rate of the drilling target combination as data bases, uses the exploration risk analysis thought as a reference, and utilizes the Monte Carlo random simulation technology to generate the oil-gas reserve distribution after future drilling of the drilling target combination. Compared with the prior art, the method fully considers the exploration risk and the resource amount distribution condition of each drilling target, utilizes the success rate of the drilling target combination experience to correct the results, replaces the former rough average estimated value by the form of the oil and gas reserve distribution after future drilling of the drilling target combination, has more scientific and reliable calculation results, embodies the quantitative risk analysis thought, and can provide important reference basis for annual exploration planning and investment combination optimization of oil companies.
The specific implementation flow of an embodiment of the present invention is shown in fig. 1. The steps illustrated in the flow charts of the drawings may be performed in a computer system such as a set of computer-executable instructions and, although a logical order is illustrated in the flow charts, in some cases, the steps illustrated or described may be performed in an order different than here.
Step S101 is first executed to construct a hydrocarbon-containing probability distribution model of a drilling target combination. In constructing the distribution model, the present invention introduces a risk analysis that takes into account the exploration risk of each drilling target. The hydrocarbon-bearing probability of each drilling target is first obtained by risk analysis of the drilling target. And then constructing a hydrocarbon-containing probability distribution model of each drilling target by adopting 0-1 distribution on the basis of the hydrocarbon-containing probability of each drilling target. In the 0-1 distribution, 0 represents drilling target future drilling failure and 1 represents drilling target future drilling success, and the probability assignments for both are the hydrocarbon-free probability of the corresponding drilling target and the hydrocarbon-containing probability of the corresponding drilling target, respectively. The steps not only consider the hydrocarbon-containing probability of the drilling target in the physical sense, but also consider the human factor of whether the drilling is successful, so that the obtained hydrocarbon-containing probability distribution model is closer to the actual situation and more reliable. The method of the invention adds quantitative risk analysis to make the final result more approximate to the actual situation.
Then, step S102 is executed to build a resource amount distribution model of the drilling target combination. In the present embodiment, a hydrocarbon resource amount distribution model of each drilling target in the drilling target combination is first constructed using a log-normal distribution. And then constructing an oil and gas resource quantity distribution model of the drilling target combination according to the oil and gas resource quantity distribution model of each drilling target.
The probability distribution model containing hydrocarbon and the distribution model of the hydrocarbon resource amount of the well-established drilling target combination can be randomly sampled (step S110). In the existing random sampling method, a monte carlo method is commonly used, which is also called as a statistical simulation method or a random sampling technology. The monte carlo method is a stochastic simulation calculation method based on probabilistic and statistical theory methods, and is a method that uses random numbers (or more commonly pseudo-random numbers) to solve many computational problems. In the prior art, the final result obtained by random sampling by adopting a Monte Carlo method is the most approximate to the actual situation. In the present embodiment, therefore, random sampling is performed based on the monte carlo method. The method of the invention utilizes random sampling to calculate and establish the oil and gas reserves distribution after drilling so as to replace the former rough average estimated value, and the acquired oil and gas reserves distribution after drilling in the future is more accurate.
The method of the invention randomly samples the distribution model for a plurality of times. In theory, the more times the random sampling, the more accurate the final result. But random sampling cannot be performed an unlimited number of times in actual practice. Therefore, before random sampling, step S104 is performed to set the number of random sampling. In this embodiment, the number of random samples is set based on the accuracy requirements of the future post-drilling hydrocarbon reserve distribution of the drilling target combination.
Next, in step S103, random numbers are generated for the two distribution models that need to be randomly sampled. Step S110 may then be performed to perform random sampling based on the random number. The random sampling process of the two distribution models will be described separately.
(1) Hydrocarbon-bearing probability distribution model for drilling target combinations
During each random sampling, step S121 is executed to record the drilling target success number of each sampling. In this embodiment, the drilling target success count for each sample is recorded by constructing a statistical variable for recording the drilling target success count. If the sampling value of the hydrocarbon-containing probability model of a certain drilling target is 1, indicating that the drilling of the drilling target of the sampling is successful, and adding 1 to the success number of the drilling target; if the sampling value of the hydrocarbon-containing probability model of a certain drilling target is 0, the drilling failure of the drilling target of the sampling is shown, and the success number of the drilling target is unchanged.
(2) Resource quantity distribution model for drilling target combination
In each random sampling process, step S122 is executed to record the sum of the drilling target hydrocarbon resource amount. Similar to step S111, in the present embodiment, the sum of the drilling target resource amounts for each sampling is recorded by constructing a statistical variable.
In this embodiment, after each random sampling is completed, step S130 is executed to determine whether the number of random samples reaches the set value. And if the random sampling times do not reach the set value, returning to the step S103 again, and respectively generating new random numbers for the two distribution models. Then, step S110 is executed by using the new random number, a new random sampling is performed on the two distribution models respectively, and step S121 and step S122 are executed to record the drilling target success number of the new random sampling and the sum of the drilling target resource amount. The loop is repeated until the random sampling times reach the set value.
And when the random sampling times reach a set value, the step of randomly sampling the distribution model is ended. And obtaining a drilling target success number sampling result and a drilling target combined resource quantity sampling result. The sampling results are then used to construct the desired distribution. Step S141 is performed first to construct a first desired distribution of drilling target success numbers according to the drilling target success number sampling results. And simultaneously performing step S142, and constructing a first expected distribution of the oil and gas reserves after drilling according to the sampling result of the drilling target combined resource amount.
Step S150 is performed next, and a correlation between the first expected distribution of the oil and gas reserves after drilling the target combination drill and the first expected distribution of the drilling target success numbers is established, that is, a correspondence between each expected value of the success numbers in the first expected distribution of the drilling target success numbers and each expected value of the oil and gas reserves in the expected first distribution of the oil and gas reserves after drilling is established.
From the statistical data after the combined drilling of the drilling targets, the mathematical expectation of the success number of the drilling targets calculated by the hydrocarbon-containing probability of each drilling target is different from the actual drilling result. But from the perspective of annual exploration program of oil companies, the drilling success rate of drilling target combinations is more stable throughout the year. Therefore, the present embodiment proceeds to step S160 to obtain a drilling target success number prediction value of the drilling target combination. In this step, the total number of drilling targets contained in the current drilling target combination is corrected based on the empirical drilling success rate value of the historical drilling target combination, so as to obtain a predicted drilling target success rate value. The method not only adds quantitative risk analysis, but also utilizes the prior historical drilling experience data, the result is closer to the actual situation, and more reliable reference basis can be provided for annual exploration planning and investment portfolio optimization of oil companies.
And step S170 is carried out on the basis of the drilling target success number predicted value obtained in the step S160, and drilling target success number expected values in the first expected distribution of the drilling target success numbers are screened. And screening expected values of the drilling target success numbers in the first expected distribution of the drilling target success numbers based on the drilling target success number predicted value so as to obtain a second expected distribution of the drilling target success numbers according with the drilling target success number predicted value.
And finally, step S180 is carried out, and the future after-drilling oil and gas reserve distribution of the drilling target combination is generated. Since the correspondence between each expected value of the success number in the first expected value of the drilling target success number and each expected value of the hydrocarbon reserve in the expected first distribution of the hydrocarbon reserve after drilling is established in step S150. Therefore, the second expected distribution of the oil and gas reserves after drilling can be obtained based on the second expected distribution of the drilling target success number generated in the step S170 by using the corresponding relation.
By integrating the implementation process of the invention, it can be easily seen that the method of the invention utilizes random sampling to calculate the oil-gas reserve distribution after drilling to replace the former rough average estimated value, and the obtained oil-gas reserve distribution after drilling in the future is more accurate. Meanwhile, the method not only utilizes the past historical drilling experience data, but also adds risk analysis, embodies the quantitative risk analysis idea, has a result closer to the actual situation, and can provide a more reliable reference basis for annual exploration planning and investment portfolio optimization of oil companies.
Next, a specific implementation process of the present embodiment will be described by a more specific embodiment.
The prediction of the oil and gas reserves after the annual drilling target combination drilling of a certain oil company is taken as an example. The drilling target combination has 21 drilling targets, and the recoverable resource content and the hydrocarbon-containing probability of the drilling targets are shown in the table 1.
TABLE 1
Firstly, an oil-gas-containing probability distribution model and an oil-gas resource amount distribution model of each drilling target are constructed.
The hydrocarbon-containing probability distribution model is constructed based on the 0-1 distribution, taking the drilling target numbered 1 as an example, and is shown in fig. 2. The bar graph labeled 0 in FIG. 2 represents the probability of failure of the drilling target numbered 1, which is 0.43; the histogram labeled 1 represents the probability of success for the drilling target numbered 1, which is 0.57.
And then respectively constructing a distribution model of the drilling target resource amount. Still taking the drilling target numbered 1 as an example, the resource amount distribution model is constructed by using the log-normal distribution according to the P10 value, the P50 value and the P90 value of the resource amount thereof as shown in fig. 3. In fig. 3, the abscissa is the amount of resources of the drilling target, and the ordinate is the cumulative probability of the corresponding amount of resources.
The hydrocarbon-containing probability distribution model and the hydrocarbon resource amount distribution model of all the drilling targets shown in table 1 were constructed in accordance with the above-described method.
In the aspect of drilling target success number prediction, the annual drilling target combination success rate empirical value of the oil company is 40%, the annual drilling target combination comprises 21 drilling targets, and the annual drilling target success number is predicted to be 8.
According to the constructed hydrocarbon-containing probability model and resource amount distribution model of each drilling target, 10000 times of Monte Carlo random simulation sampling is carried out, and a first expected distribution (figure 4) of the drilling target success number and a first expected distribution (figure 5) of the reserve after future drilling of the drilling target combination are respectively generated by counting the sum of the drilling target success number and the resource amount of each drilling target sampled in each round. And establishing a correlation between the two distributions, and recording the drilling target success number corresponding to each reserve expected value in the first expected distribution (figure 5) of the reserves after the drilling target combination is drilled in the future, wherein the first expected distribution (figure 4) of the reserves corresponds to the drilling target success number.
And filtering the first expected distribution (figure 4) of the drilling target success numbers according to the drilling target success number predicted values (8) to obtain a second expected distribution of the drilling target success numbers which accords with the 8 drilling target success numbers. And generating a second expected distribution of the future after-drilling reserves of the drilling target combination based on the corresponding relation between the success number of the drilling target and the future after-drilling reserves of the drilling target combination, so as to form a final after-drilling reserves distribution of the drilling target combination, wherein the final result is shown in fig. 6.
According to the method of the invention, the final result is a probability distribution. Whereas the corresponding result obtained by the conventional method is a certain unique value. Compared with the traditional method, the method provided by the invention has the advantage that the obtained result is closer to the actual situation. Take the specific example in fig. 6 as an example. In fig. 6, the future post-drilling reserve corresponding to the accumulation probability of 90% is 1117.27 ten thousand tons, the future post-drilling reserve corresponding to the accumulation probability of 10% is 2208.03 ten thousand tons, and the Mean (Mean) is 1614.38 ten thousand tons. The result obtained based on the prior art method was 1882.51 ten thousand tons. After the batch of pre-exploration targets are combined, the well drilling proves that the petroleum recoverable reserves are found to be 1512 ten thousand tons, and the prediction result is basically consistent with (and is more approximate to) the prediction result of the invention.
Although the embodiments of the present invention have been described above, the above description is only for the convenience of understanding the present invention, and is not intended to limit the present invention. The method of the present invention may have other embodiments, and those skilled in the art can make various changes and modifications according to the present invention without departing from the spirit of the present invention, and these changes and modifications should fall within the protection scope of the claims of the present invention.
Claims (6)
1. A method of obtaining a future post-drilling hydrocarbon reserve distribution for a drilling target combination, the method comprising the steps of:
step one, constructing a first expected distribution of drilling target success numbers of the drilling target combination and a first expected distribution of oil and gas reserves after drilling of the drilling target combination, wherein the first expected distribution comprises the following steps:
acquiring the hydrocarbon-bearing probability of each drilling target in the drilling target combination;
constructing a hydrocarbon-bearing probability distribution model of the drilling target combination by adopting 0-1 distribution according to the hydrocarbon-bearing probability of each drilling target, wherein in the 0-1 distribution, 0 represents future drilling failure of the drilling target, and 1 represents future drilling success of the drilling target;
randomly sampling the hydrocarbon-containing probability distribution model to obtain a drilling target success number sampling result;
constructing a first expected distribution of the drilling target success number according to the drilling target success number sampling result;
adopting lognormal distribution to construct an oil and gas resource quantity distribution model of each drilling target, and thus constructing an oil and gas resource quantity distribution model of the drilling target combination according to the oil and gas resource quantity distribution model of each drilling target;
randomly sampling the oil and gas resource quantity distribution model of the drilling target combination so as to obtain a resource quantity sampling result;
constructing expected first distribution of the oil and gas reserves after drilling according to the sampling result of the drilling target combined resource amount;
step two, obtaining a drilling target success number predicted value of the drilling target combination;
establishing an incidence relation between the first expected distribution of the drilling target success number and the first expected distribution of the oil and gas reserves after drilling;
screening the first expected distribution of the drilling target success numbers based on the drilling target success number predicted value so as to obtain a second expected distribution of the drilling target success numbers;
and fifthly, acquiring second expected distribution of the oil and gas reserves after drilling corresponding to the second expected distribution of the drilling target success number based on the incidence relation, so as to form the oil and gas reserves after drilling in the future according to the second expected distribution of the oil and gas reserves after drilling, and further optimize the annual exploration plan of the oil company.
2. The method of claim 1 wherein in step three, a correspondence is established between each expected value of success number in the drilling target success number first desired distribution and each expected value of hydrocarbon reserve in the post-drilling hydrocarbon reserve first desired distribution.
3. The method according to claim 1, wherein in step two, the drilling target success number predicted value is obtained based on drilling success rate empirical values of historical drilling target combinations.
4. The method of claim 1 wherein said hydrocarbon-bearing probability distribution model is randomly sampled a plurality of times, wherein:
setting the number of times of the random sampling based on the accuracy requirement of future post-drilling hydrocarbon reserve distribution of the drilling target combination;
recording the drilling target success number of each random sampling, thereby generating the drilling target success number sampling result.
5. The method of claim 4, wherein in the random sampling process, if the sampling value of the hydrocarbon-bearing probability distribution model is 1, it indicates that the drilling target of the sampling is successfully drilled, and the drilling target success number is increased by 1; if the sampling value of the hydrocarbon-containing probability distribution model is 0, the drilling failure of the sampling drilling target is represented, and the success number of the drilling target is unchanged.
6. The method of claim 1, wherein the hydrocarbon resource quantity distribution model of the drilling target combination is randomly sampled a plurality of times, wherein:
setting the number of times of the random sampling based on the accuracy requirement of future post-drilling hydrocarbon reserve distribution of the drilling target combination;
recording the sum of the resource amount of each drilling target sampled at each time randomly, thereby generating the drilling target combined resource amount sampling result.
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| CN101295373A (en) * | 2007-04-24 | 2008-10-29 | 中国石油天然气股份有限公司 | Method for deciding oil gas drilling by net present value after geologic risk |
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| CN103295073A (en) * | 2012-03-05 | 2013-09-11 | 北京凯圣特经济技术发展有限公司 | Oil-gas exploration prediction and oil reservoir collaborative management decision method |
| CN103714390A (en) * | 2012-09-28 | 2014-04-09 | 中国石油化工股份有限公司 | Oil and gas trap combination exploration optimization method |
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| CN101295373A (en) * | 2007-04-24 | 2008-10-29 | 中国石油天然气股份有限公司 | Method for deciding oil gas drilling by net present value after geologic risk |
| CN103116186A (en) * | 2011-11-16 | 2013-05-22 | 中国石油天然气集团公司 | Determination method for small-scale heterogeneous collective volume |
| CN103295073A (en) * | 2012-03-05 | 2013-09-11 | 北京凯圣特经济技术发展有限公司 | Oil-gas exploration prediction and oil reservoir collaborative management decision method |
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