Method for evaluating formation testing and selection of low-permeability reservoir

Abstract

The invention relates to the technical field of low-permeability oil and gas reservoir formation testing and selection methods, in particular to a low-permeability reservoir formation testing and selection evaluation method which comprises the steps that a nuclear magnetic resonance experiment is conducted on a fresh rock sample every one hour; and calculating the content of the light hydrocarbon component in the total porosity according to the total porosity when the core is just taken out of the cylinder and the total porosity of the last nuclear magnetic resonance experiment, then calculating the dispersion loss coefficient X of the light hydrocarbon component, and establishing a low-permeability reservoir formation testing layer selection chart according to the formation testing result of the tested oil well and the dispersion loss coefficient X of the light hydrocarbon component. The method has the advantages that the dispersion loss coefficient of the light hydrocarbon component is calculated by utilizing a nuclear magnetic resonance full-diameter rock core experiment, the permeability and the oil-gas possibility of the rock core are dynamically reflected, and the problem of large difference of experimental results of manual rock sample selection is avoided. And through contrastive analysis of the dispersion loss coefficient of the light hydrocarbon component and an oil testing result, a low-permeability reservoir oil testing layer selection chart is established, oil testing layer selection of the low-permeability reservoir is guided, and the oil and gas obtaining rate of oil testing is increased.

Description

Technical Field

[0001] The invention relates to the technical field of low permeability oil and gas reservoir oil testing and layer selection methods, and is a low permeability reservoir oil testing and layer selection evaluation method. Background Art

[0002] Well oil testing is an important part of exploration and production, and the discussion of oil testing plans is the primary task of well oil testing. At present, the important task in the discussion of oil testing plans is to analyze and predict the oil testing conclusions of the wells to be tested, and to select the test layers according to the expected oil testing results. Generally speaking, only oil and gas layers with industrial exploitation value will be put into oil testing and fracturing. In order to increase the oil and gas yield rate of oil testing and avoid the cost waste caused by not obtaining oil and gas flow, layer selection before oil testing is particularly important. With the continuous deepening of exploration and development, complex lithology, low porosity and low permeability reservoirs have become the main objects of exploration and development. Due to the complexity and concealment of the reservoirs, it is becoming increasingly difficult to judge the results of oil testing.

[0003] The Chinese patent application document with application number 201310088247.9 discloses a reservoir gas production prediction method and device based on pore analysis. This method selects at least one full-diameter core in the target layer section, obtains CT test data of each full-diameter core (including the total number of core slices and the total area of ​​each core slice), and then calculates the porosity of each full-diameter core according to the CT test data, and predicts the production of the target layer section according to the average value of all target porosities, and then determines the gas production level. This method uses the porosity that reflects the characteristics of the reservoir itself to predict the production, excludes the influence of engineering factors, and does not consider the influence of other parameters such as permeability and gas saturation on production capacity. The calculation result is not accurate enough and has certain limitations in application.

[0004] The Chinese patent application document with application number 201510142449.6 discloses a method and system for establishing a reservoir capacity prediction model. The method is to analyze the existing core capacity simulation data, use the relevant attributes of the reservoir's own characteristics to determine the reservoir characteristic parameters with the best correlation with production to participate in the fitting modeling, classify and establish model relationships, and then select the model relationship that meets the actual situation of the target reservoir from the well logging gas test data as the reservoir capacity prediction model. This method requires the collection of core porosity, permeability and other data. Due to the strong heterogeneity of low-permeability reservoirs, the sampling on the full-diameter core is greatly affected by human factors. The porosity and permeability data obtained at different sampling locations are greatly different, which will cause large prediction errors in the capacity prediction model.

[0005] At present, the core parameters used in oil production selection for capacity prediction testing mainly include porosity, permeability, pore-to-roar ratio, average capillary radius and other parameters, which need to be manually selected and then obtained through experiments. However, it is not easy to obtain dynamic parameters such as permeability and saturation under original formation conditions through full-diameter core experiments. There is an urgent need for a low-permeability reservoir oil selection method that includes parameters reflecting reservoir dynamics and is not affected by manual sampling. Summary of the invention

[0006] The present invention provides a low permeability reservoir oil testing and layer selection evaluation method, which overcomes the shortcomings of the above-mentioned prior art and can effectively solve the problems that the existing oil testing and layer selection evaluation method is difficult to dynamically reflect the permeability and oil and gas content of the core, and the experimental results of artificial rock selection samples vary greatly.

[0007] The technical solution of the present invention is achieved by the following measures: A method for evaluating the oil testing and layer selection of a low permeability reservoir, comprising the following steps:

[0008] The first step is to take a fresh core sample immediately after the core is taken out of the barrel, conduct a full-diameter nuclear magnetic resonance rock sample experiment, and measure the T2 spectrum of the fresh rock sample (fresh core sample);

[0009] The second step is to place the fresh rock sample at normal pressure, constant temperature and the same humidity, and conduct a nuclear magnetic resonance experiment every hour to obtain T2 spectra at different time stages. When the T2 spectrum does not change much, stop the nuclear magnetic resonance experiment and record the total standing time t of the rock sample.

[0010] The third step is to calculate the total porosity φ of the NMR experiment when the core is just out of the tube (i.e. the NMR full-diameter rock sample experiment). 总 , and then calculate the total porosity φ′ of the last NMR experiment after the light hydrocarbon components are lost 总 , according to the total porosity φ of the core just out of the tube 总 and the total porosity φ′ from the last NMR experiment 总 Calculate the content of light hydrocarbon components in the total pores;

[0011] The fourth step is to calculate the light hydrocarbon component dispersion coefficient X according to the estimated value of the formation pressure P at the downhole coring position, the content of the light hydrocarbon component in the total pores and the total static time t of the rock sample;

[0012] The fifth step is to collect the oil test results of the tested wells in the same exploration area and the same layer, compare them with the dispersion loss coefficient X of the light hydrocarbon component, and establish a low permeability reservoir oil test layer selection chart.

[0013] The following are further optimizations and / or improvements to the above technical solutions:

[0014] For the Permian low-permeability reservoir in the Xiayan area, when 0≤X≤4, the reservoir is a water layer or a dry layer; when 4<X≤6, the reservoir is an oil-bearing layer or a gas-bearing layer; when 6<X≤10, the reservoir is an oil and gas layer; when 10<X≤12, the reservoir is a gas layer.

[0015] In the second step, the T2 spectrum does not vary much, specifically, the T2 spectrum data errors of the last two experiments are ≤10%.

[0016] The calculation formula for the content of the above light hydrocarbon components in the total pores is as follows:

[0017]

[0018] In the formula, v 总 Represents the content of light hydrocarbon components in the total pores.

[0019] The calculation formula for the dispersion coefficient of the above light hydrocarbon components is as follows:

[0020]

[0021] Where X represents the dispersion coefficient of light hydrocarbon components, v 总 It represents the content of light hydrocarbon components in the total pores, P represents the estimated formation pressure at the coring location, and t represents the total static time of the rock sample in the NMR experiment. It reflects the amount of oil and gas lost per unit pressure difference (the difference between the pressure at the coring location and the normal pressure) per unit time. The larger the loss coefficient X, the more and faster the light hydrocarbon components will be lost.

[0022] The advantage of the present invention is that it uses the full-diameter core experiment of nuclear magnetic resonance to calculate the dispersion coefficient of light hydrocarbon components, dynamically reflects the permeability and oil and gas content of the core, and avoids the problem of large differences in the experimental results of artificial rock selection. By comparing and analyzing the dispersion coefficient of light hydrocarbon components with the results of oil testing, a low-permeability reservoir oil testing layer selection chart is established to guide the oil testing layer selection of low-permeability reservoirs and improve the oil and gas yield of oil testing. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Attached Figure 1 This is the T2 spectrum of fresh rock sample (0 hours).

[0024] Attached Figure 2 This is the T2 spectrum of fresh rock sample (1 hour).

[0025] Attached Figure 3 This is the T2 spectrum of fresh rock sample (2 hours).

[0026] Attached Figure 4 This is the T2 spectrum of fresh rock sample (3 hours).

[0027] Attached Figure 5 This is the T2 spectrum of fresh rock sample (4 hours).

[0028] Attached Figure 6 This is the layer selection chart for oil testing in the Permian low-permeability reservoir in the Xiayan area. DETAILED DESCRIPTION

[0029] The present invention is not limited by the following embodiments, and specific implementation methods can be determined based on the technical solution of the present invention and actual conditions.

[0030] In the present invention, the nuclear magnetic resonance experiment refers to the nuclear magnetic resonance full-diameter rock sample experiment.

[0031] The present invention will be further described below in conjunction with embodiments:

[0032] Embodiment 1: The method for evaluating the low permeability reservoir oil testing and layer selection comprises the following steps:

[0033] The first step is to take a fresh core sample immediately after the core is taken out of the barrel, conduct a full-diameter nuclear magnetic resonance rock sample experiment, and measure the T2 spectrum of the fresh rock sample (fresh core sample);

[0034] The second step is to place the fresh rock sample at normal pressure, constant temperature and the same humidity, and conduct a nuclear magnetic resonance experiment every hour to obtain T2 spectra at different time stages. When the T2 spectrum does not change much, stop the nuclear magnetic resonance experiment and record the total standing time t of the rock sample.

[0035] The third step is to calculate the total porosity φ of the NMR experiment when the core is just out of the tube (i.e. the NMR full-diameter rock sample experiment). 总 , and then calculate the total porosity φ′ of the last NMR experiment after the light hydrocarbon components are lost 总 , according to the total porosity φ of the core just out of the tube 总 and the total porosity φ′ from the last NMR experiment 总 Calculate the content of light hydrocarbon components in the total pores;

[0036] The fourth step is to calculate the light hydrocarbon component dispersion coefficient X according to the estimated value of the formation pressure P at the downhole coring position, the content of the light hydrocarbon component in the total pores and the total static time t of the rock sample;

[0037] The fifth step is to collect the oil test results of the tested wells in the same exploration area and the same layer, compare them with the dispersion loss coefficient X of the light hydrocarbon component, and establish a low permeability reservoir oil test layer selection chart.

[0038] Subsequently, the light hydrocarbon component dispersion coefficient X can be calculated according to the nuclear magnetic resonance full-diameter rock sample experiment, and the reservoir properties can be determined by X on the low-permeability reservoir oil test layer selection chart, that is, the reservoir can be determined as: water layer, dry layer, oil-bearing layer, gas-bearing layer, oil and gas layer or gas layer.

[0039] Example 2: As an optimization of the above example, in the second step, the T2 spectrum does not vary much, specifically, the T2 spectrum data error of the last two experiments is ≤10%.

[0040] Example 3: As an optimization of the above example, the content of light hydrocarbon components in the total pores is calculated as follows:

[0041]

[0042] In the formula, v 总 Represents the content of light hydrocarbon components in the total pores.

[0043] Example 4: As an optimization of the above example, the light hydrocarbon component dispersion coefficient calculation formula is as follows:

[0044]

[0045] Where X represents the dispersion coefficient of light hydrocarbon components, v 总 represents the content of light hydrocarbon components in the total pores, P represents the estimated formation pressure at the coring position downhole, and t represents the total static time of the rock sample in the nuclear magnetic resonance experiment.

[0046] After the core is taken out of the barrel, under normal pressure conditions, the light oil and gas components will volatilize. The amount and speed of volatilization of light components are related to the permeability and content of light components in the core. The better the core permeability, the higher the content of light components in the core, and the faster and more light components evaporate. At the same time, the better the core permeability and the higher the content of light components, the greater the probability of obtaining industrial oil and gas flow in oil testing. By evaluating the content and volatilization speed of light components in the core, the relationship with the wells that obtain industrial oil and gas flow is established, and the selection of layers for oil testing in low-permeability reservoirs is achieved.

[0047] In the present invention, after the fresh core is taken out of the barrel, a nuclear magnetic resonance full-diameter core experiment is carried out, the core is left to stand for a period of time to allow the light hydrocarbon components to volatilize, and then the nuclear magnetic resonance full-diameter core experiment is carried out. The dispersion coefficient of the light hydrocarbon component is calculated through the nuclear magnetic resonance experimental data, and the dynamic evaluation parameter is compared with the tested oil wells to establish a low permeability reservoir oil test layer selection chart.

[0048] Implementation Cases

[0049] The first step is to drill and coring the X36 well at 4200 meters in the Permian system of Xiayan area on the northwest edge of the Junggar Basin. Fresh core samples were immediately taken out for full-diameter nuclear magnetic resonance rock sample testing, and the T2 spectrum of fresh rock samples was measured ( Figure 1 ).

[0050] In the second step, the fresh rock sample was placed in the laboratory at the drilling site, and allowed to stand for 1 hour under normal pressure (atmospheric pressure), constant temperature (constant temperature 20°C), and humidity 60%. A nuclear magnetic resonance experiment was performed to measure the T2 spectrum ( Figure 2 ),and Figure 1 (0 hours) T2 spectra comparison, found that the two T2 spectra are different, reflecting the light hydrocarbon components are constantly lost. Then another NMR experiment was performed 1 hour later, and the last two T2 spectra were compared ( Figure 4-Figure 5 ), at the 3rd and 4th hours, the T2 spectrum did not change much (≤10%), the NMR experiment was stopped, and the total standing time t of the rock sample was recorded as 4 hours.

[0051] The third step is to calculate the total NMR porosity φ when the core is just out of the tube (0 hours) based on the NMR experiment. 总 It is 11.28%, the total NMR porosity of the core out of the barrel (4 hours) is 10.14%, and the content of light hydrocarbon components in the total NMR porosity is 10.11%.

[0052] Step 4: Calculate the dispersion coefficient of light hydrocarbon components. Well X36 is at 4200 meters, with an estimated formation pressure of 53.56 MPa, and the dispersion coefficient X is calculated to be 4.72.

[0053] In the fifth step, the oil test results of 20 tested oil layers in the Permian system in the Xiayan area on the northwest edge of the Junggar Basin were collected, and the oil test results were compared with the loss coefficient X to establish the oil test layer selection chart for the Permian low-permeability reservoir in the Xiayan area ( Figure 6 ).

[0054] Depend on Figure 6 It can be seen that for the Permian low-permeability reservoir in the Xiayan area, when 0≤X≤4, the reservoir is a water layer or a dry layer; when 4<X≤6, the reservoir is an oil-bearing layer or a gas-bearing layer; when 6<X≤10, the reservoir is an oil and gas layer; when 10<X≤12, the reservoir is a gas layer.

[0055] The above technical features constitute the embodiments of the present invention, which have strong adaptability and implementation effect. Non-essential technical features can be added or reduced according to actual needs to meet the requirements of different situations.

Claims

1. A method for evaluating the oil layer selection in a low permeability reservoir, characterized in that The following steps are involved: The first step is to take fresh core samples immediately after the core is taken out of the barrel, conduct a full-diameter nuclear magnetic resonance rock sample experiment, and measure the T2 spectrum of the fresh rock sample; The second step is to place the fresh rock sample at normal pressure, constant temperature and the same humidity, and conduct a nuclear magnetic resonance experiment every hour to obtain T2 spectra at different time stages. When the T2 spectrum does not change much, stop the nuclear magnetic resonance experiment and record the total standing time t of the rock sample. The third step is to calculate the total porosity φ of the NMR experiment when the core is just out of the tube. 总 , and then calculate the total porosity φ′ of the last NMR experiment after the light hydrocarbon components are lost 总 , according to the total porosity φ of the core just out of the tube 总 and the total porosity φ′ from the last NMR experiment 总 Calculate the content of light hydrocarbon components in the total pores; The fourth step is to calculate the light hydrocarbon component dispersion coefficient X according to the estimated value of the formation pressure P at the downhole coring position, the content of the light hydrocarbon component in the total pores and the total static time t of the rock sample; The fifth step is to collect the oil test results of the tested wells in the same exploration area and the same layer, compare them with the dispersion loss coefficient X of the light hydrocarbon component, and establish a low permeability reservoir oil test layer selection chart.

2. The method for evaluating the low permeability reservoir oil testing and layer selection according to claim 1, characterized in that For the Permian low-permeability reservoir in the Xiayan area, when 0≤X≤4, the reservoir is a water layer or a dry layer; when 4<X≤6, the reservoir is an oil-bearing layer or a gas-bearing layer; when 6<X≤10, the reservoir is an oil and gas layer; when 10<X≤12, the reservoir is a gas layer.

3. The low permeability reservoir oil testing layer selection evaluation method according to claim 1 or 2, characterized in that The calculation formula for the content of light hydrocarbon components in the total pores is as follows: In the formula, v 总 Represents the content of light hydrocarbon components in the total pores.

4. The method for evaluating the low permeability reservoir oil testing and layer selection according to claim 1 or 2, characterized in that In the second step, the T2 spectrum does not vary much, specifically, the T2 spectrum data errors of the last two experiments are ≤10%.

5. The method for evaluating the low permeability reservoir oil testing and layer selection according to claim 3 is characterized in that In the second step, the T2 spectrum does not vary much, specifically, the T2 spectrum data errors of the last two experiments are ≤10%.

6. The method for evaluating the low permeability reservoir oil testing and layer selection according to claim 1 or 2, characterized in that The calculation formula of the dispersion coefficient of light hydrocarbon components is as follows: Where X represents the dispersion coefficient of light hydrocarbon components, v 总 represents the content of light hydrocarbon components in the total pores, P represents the estimated formation pressure at the coring position downhole, and t represents the total static time of the rock sample in the nuclear magnetic resonance experiment.

7. The method for evaluating the low permeability reservoir oil testing and layer selection according to claim 3 is characterized in that The calculation formula of the dispersion coefficient of light hydrocarbon components is as follows: Where X represents the dispersion coefficient of light hydrocarbon components, v 总 represents the content of light hydrocarbon components in the total pores, P represents the estimated formation pressure at the coring position downhole, and t represents the total static time of the rock sample in the nuclear magnetic resonance experiment.

8. The method for evaluating the oil layer selection in a low permeability reservoir according to claim 4, characterized in that The calculation formula of the dispersion coefficient of light hydrocarbon components is as follows: Where X represents the dispersion coefficient of light hydrocarbon components, v 总 represents the content of light hydrocarbon components in the total pores, P represents the estimated formation pressure at the coring position downhole, and t represents the total static time of the rock sample in the nuclear magnetic resonance experiment.

9. The method for evaluating the low permeability reservoir oil testing and layer selection according to claim 5, characterized in that The calculation formula of the dispersion coefficient of light hydrocarbon components is as follows: Where X represents the dispersion coefficient of light hydrocarbon components, v 总 represents the content of light hydrocarbon components in the total pores, P represents the estimated formation pressure at the coring position downhole, and t represents the total static time of the rock sample in the nuclear magnetic resonance experiment.

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