A method for quickly identifying watered-out layers and judging watered-out levels based on carbon-oxygen ratio logging

Abstract

The present invention provides a method for quickly identifying water-flooded layers and determining water-flooding levels based on carbon-oxygen ratio logging, including: Step 1, determining the formation porosity; Step 2, calculating the theoretical water line; Step 3, calculating the theoretical oil line; Step 4, quickly qualitatively identifying water-flooded layers; Step 5, establishing a water-flooding level identification chart. The present invention can quickly qualitatively identify water-flooded layers by overlapping the oil line, water line and carbon-oxygen ratio curve on the same scale. By constructing a water-flooding level identification factor, the influence of lithology and porosity changes on the carbon-oxygen ratio logging value is eliminated, highlighting the fluid response characteristics. The accuracy of water-flooding level judgment is higher and the universality is strong. The method can be applied to the data interpretation of all measurements of carbon-oxygen ratio curves and silicon-calcium ratio curves, such as carbon-oxygen ratio logging and pulsed neutron full-spectrum saturation logging.

Description

Technical Field

[0001] The present invention belongs to the fields of geophysical logging and oilfield development; in particular, it relates to a method for quickly identifying watered-out zones and judging watered-out levels based on carbon-oxygen ratio logging. Background Art

[0002] In the middle and late stages of oilfield development, the monitoring of remaining oil saturation is of great significance for increasing oil reserves, enhancing production, stabilizing oil production, and controlling water cut. With the continuous development of oilfields, many oilfields have entered the middle and late stages of development, and the reservoir water flooding situation is relatively serious. Although a large amount of oil resources have been produced, there are still a considerable number of remaining oil resources that have not been produced. The distribution law of remaining oil is complex, and the high-water-cut areas and low-water-cut areas are unevenly distributed. How to adjust the oilfield development plan, control water and stabilize oil production, and tap the potential of old wells has become an urgent problem to be solved in oilfield development.

[0003] Carbon-oxygen ratio (C / O) logging is an important method for measuring oil saturation through casing and evaluating watered-out zones. Based on the theory of fast neutron inelastic scattering, this method has the advantage of being able to penetrate media such as the instrument housing, well fluid, steel casing, and cement sheath and directly detect the formation. Its measurement results are basically independent of the salinity of formation water. Therefore, carbon-oxygen ratio (C / O) logging can directly distinguish oil layers from water layers with low salinity, unknown salinity, or large salinity changes in cased wells, and it is one of the most effective methods for determining remaining oil saturation in onshore oilfield cased wells.

[0004] In recent years, carbon-oxygen ratio logging has played a very important role in dividing watered-out levels and determining remaining oil saturation. The in-depth exploration and development of oilfields have further expanded the application scope of carbon-oxygen ratio (C / O) logging, such as the evaluation of watered-out zones and the monitoring of remaining oil saturation, and good geological effects have been achieved. In the interpretation of watered-out zones, the currently commonly used qualitative identification method for judging watered-out zones is to use the overlap of carbon-oxygen ratio and silicon-calcium ratio logging curves to identify watered-out zones, and use the carbon-oxygen ratio and silicon-calcium ratio crossplot to identify watered-out levels. However, when the formation porosity and lithology change, the application effect is poor. Therefore, there is an urgent need for a method that can solve the deficiencies of the above-mentioned existing technologies. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for quickly identifying watered-out zones and judging watered-out levels based on carbon-oxygen ratio logging.

[0006] The present invention is achieved through the following technical solutions:

[0007] The present invention relates to a method for quickly identifying watered-out zones and judging watered-out levels based on carbon-oxygen ratio logging, including the following steps:

[0008] Step 1: Determine the formation porosity;

[0009] Step 2: Calculate the theoretical water line;

[0010] Step 3: Calculate the theoretical oil line;

[0011] Step 4: Rapid qualitative identification of water - flooded zones;

[0012] Step 5: Establish a recognition chart for water - flooding levels.

[0013] Preferably, in Step 1, the specific steps for determining the formation porosity are as follows: The formation porosity (POR) can be obtained by calculating using the theoretical formula or the regression formula of core - calibrated logging from the three - porosity logging curves (DT, DEN, CNL) of conventional logging data (source: Yong Shihe, Zhang Chaomo. Logging Data Processing and Comprehensive Interpretation [M]. Petroleum University Press, 1996.), or can be obtained using nuclear magnetic resonance logging data;

[0014] Preferably, in Step 2, the specific steps for calculating the theoretical water line are as follows: Select a water layer section with relatively pure lithology, no calcite, and low shale content, plot the cross - plot of carbon - oxygen ratio (C / O) versus silicon - calcium ratio (Si / Ca), find the best water line, and regress to obtain the slope Kw and intercept Iw of the water line. Then, the water line value (COW) at any depth point can be calculated by combining the silicon - calcium ratio curve with the regressed slope and intercept. Water layers can be found with the help of conventional logging curves.

[0015] Preferably, in Step 3, the specific steps for calculating the theoretical oil line are as follows: There is a good corresponding relationship between the distance between the oil line and the water line and the porosity. The difference (△C / O) between the two can be expressed as 0.6×POR in terms of porosity 1.11 , so the oil line value (COO) at any depth point can be calculated from the porosity and water line value at the corresponding depth point, and COO = COW + △C / O;

[0016] Preferably, in Step 4, the specific steps for the rapid qualitative identification of water - flooded zones are as follows: Conduct curve comparison. Place the oil line, water line, and carbon - oxygen ratio curve in the same track and display them with the same scale. If the formation is not water - flooded, the C / O curve and the COO curve basically coincide and deviate far from the COW curve; if the formation is water - flooded, the C / O curve and the COO curve deviate. The degree of deviation is related to the degree of water - flooding. The more severe the water - flooding, the farther the C / O curve and the COO curve deviate and the closer they are to the COW curve.

[0017] Preferably, in Step 5, the specific steps for establishing the recognition chart for water - flooding levels are as follows:

[0018] S1: Calculate the water flooding level identification factors X and Y: The identification factor X is defined as the difference between the C / O curve and the COW curve, and the identification factor Y is defined as the difference between the COO curve and the C / O curve. Read the COO curve, COW curve, and C / O curve corresponding to different water flooding levels respectively according to the test data, and calculate the identification factors.

[0019] S2: Analyze the water flooding level of the perforated interval by using the production performance data and the water plugging effect, and make a water flooding level identification chart in combination with the water flooding level identification factors in S1.

[0020] The present invention has the following advantages:

[0021] (1) The method of the present invention realizes the rapid identification of water flooded layers through the overlapping comparison of the C / O, COO, and COW curves;

[0022] (2) The method of the present invention can eliminate the influence of lithology changes and physical property changes on the measured values through the water flooding level identification factors X and Y, highlighting the response characteristics of fluids, and thus the established water flooding level identification chart has stronger adaptability.

[0023] (3) The method of the present invention can be applied to the data interpretation of all measurements of carbon-oxygen ratio curves and silicon-calcium ratio curves, such as carbon-oxygen ratio logging and pulsed neutron full-spectrum saturation logging. The present invention has a wide application range and good prospects. Description of the Drawings

[0024] Figure 1 It is a core calibration density curve (DEN) porosity calculation chart;

[0025] Figure 2 It is a C / O and Si / Ca cross plot;

[0026] Figure 3 It is the water flooding level identification chart established by the present invention;

[0027] Figure 4 It is the processing result chart of the actual well data in the present invention;

[0028] Figure 5 It is the landing position chart of the water flooding level identification factor of Layer 1;

[0029] Figure 6 It is the landing position chart of the water flooding level identification factor of Layer 4. Detailed Embodiments

[0030] The present invention will be described in detail below in conjunction with specific embodiments. It should be noted that the following embodiments are only further descriptions of the present invention, but the protection scope of the present invention is not limited to the following embodiments.

[0031] Embodiment

[0032] This embodiment relates to a method for quickly identifying the water flooding level based on carbon-oxygen ratio logging, including the following steps:

[0033] Step 1. Determine the formation porosity: The formation porosity (POR) can be obtained by calculating using the theoretical formula or the core-scale logging regression formula with the three porosity logging curves (DT, DEN, CNL) of conventional logging data, or by using nuclear magnetic resonance logging data. In this example, based on "core-scale logging", the formation porosity (POR) is calculated by regressing the core experimental porosity and the density curve (DEN), as Figure 1 shown, the formation porosity can be obtained: POR = -58.327×DEN + 154.86;

[0034] Step 2. Calculate the theoretical water line: Select a water layer section with relatively pure lithology, no calcite, and low shale content. The water layer can be found with the help of conventional logging curves. Plot the crossplot of carbon-oxygen ratio (C / O) and silicon-calcium ratio (Si / Ca), as shown in Figure 2 shown; and add a linear trend line to obtain the regression formula. Then, the slope of the water line can be obtained as -0.1499 and the intercept of the water line as 0.4642. Thus, the water line value (COW) at any depth point can be calculated by combining the silicon-calcium ratio curve with the regression slope and intercept. In this example, the water line calculation formula is: COW = -0.1499×Si / Ca + 0.4642;

[0035] Step 3. Calculate the theoretical oil line: There is a good corresponding relationship between the distance between the oil line and the water line and the porosity. The difference (△C / O) between the two can be expressed as 0.6×POR 1.11 , so the oil line value (COO) at any depth point can be calculated from the porosity at the current depth point and the water line value (calculated in Step 2), COO = COW + △C / O;

[0036] Step 4. Quick identification of water flooded layers: Curve comparison. Place the oil line, water line, and carbon-oxygen ratio measurement curves in the same track and display them with the same scale. If the formation is not water flooded, the C / O curve and the COO curve basically coincide and deviate far from the COW curve; if the formation is water flooded, the C / O curve and the COO curve deviate. The degree of deviation is related to the water flooding degree. The more serious the water flooding, the farther the C / O curve and the COO curve deviate and the closer they are to the COW curve.

[0037] Step 5. Establish a water flooding level identification chart. The specific steps are as follows:

[0038] S1: Calculate the water flooding level identification factors X and Y: The identification factor X is defined as the difference between the C / O curve and the COW, and the identification factor Y is defined as the difference between the COO and the C / O curve. According to the test data, read the COO curve, COW curve, and C / O ratio curve corresponding to different water flooding levels respectively, and calculate the identification factors.

[0039] S2: Use the production dynamic data and the water shutoff effect to analyze the water flooding level of the perforated interval, and combine the water flooding level identification factors in S1 to make a water flooding level identification chart. As shown in Figure 3 it can be seen that the high water flooding, medium water flooding, and low water flooding data points determined by the identification factors fall in different regions of the chart respectively.

[0040] Step 6: Application of actual well data: In order to verify the accuracy of the remaining oil saturation calculation method, process and interpret the water flooded wells in the study area. The interpretation result chart is shown in Figure 4 ; Figure 4 In the first track, there are lithology logging series tracks, including the natural gamma ray (GR), spontaneous potential (SP), and caliper (CAL) curves. The second track is the resistivity logging series track, including the deep lateral (RD), shallow lateral (RS), and microspherically focused (RXO) resistivity curves. The third track is the porosity logging series track, including the acoustic logging (DT), density logging (DEN), and neutron logging (CNL) curves. The fourth track is the carbon oxygen ratio (C / O) curve and the oil line (COO) and water line (COW) calculated by the present invention. The fifth track is the lithology profile track. Using the methods described in Step 1, Step 2, and Step 3, the water line value (COW) and the oil line value (COO) can be calculated. Using the method described in Step 4, a quick qualitative judgment of the water flooding situation of the interpreted horizons can be made. All of the No. 1-6 horizons are water flooded to varying degrees. According to the water flooding level identification chart established in Step 5, it is judged that the No. 1 and 2 horizons are medium water flooded, the No. 3 horizon is high water flooded, and the No. 4, 5, and 6 horizons are low water flooded. Combining with the production dynamic data for analysis, the original production interval of this example well was single-layer production of the No. 1 horizon, with a water production rate of 75%, belonging to medium water flooding. After that, measures were taken to plug the No. 1 horizon with cement and perforate the No. 4 horizon. After the measures, the No. 4 horizon was single-layer production, with a water production rate of 28%, belonging to low water flooding.

[0041] Combined with the water flooding level identification chart constructed by the present invention, the fluid identification factor intersection point of the No. 1 horizon is located in the medium water flooding area (see Figure 5 ), and the fluid identification factor intersection point of the No. 4 horizon is located in the low water flooding area (see Figure 6 ). The identification result of the chart is completely consistent with the result of the production dynamic data, which proves the accuracy and adaptability of the method for judging the water flooding level proposed by the present invention.

[0042] In summary, the method of the present invention realizes the rapid identification of water-flooded layers through the overlapping comparison of C / O, COO, and COW curves; the method of the present invention can eliminate the influence of lithology changes and physical property changes on the measured values through the water-flooded level identification factors X and Y, highlighting the response characteristics of fluids, and thus the established water-flooded level identification chart has stronger adaptability. The method of the present invention can be applied to the data interpretation of all measurements of C / O curves and Si / Ca ratio curves, such as carbon oxygen ratio logging and pulsed neutron full-spectrum saturation logging. The present invention has a wide application scope and good prospects. Any method that uses the overlapping method of the C / O, COW, and COW curves and the cross-plot technology of the water-flooded level identification factors X and Y to rapidly identify water-flooded layers and determine the water-flooded level should be protected.

[0043] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various deformations or modifications within the scope of the claims, which does not affect the essence of the present invention.

Claims

1. A method for quickly identifying water - flooded layers and judging the water - flooding level based on carbon - oxygen ratio logging, characterized in that, it includes the following steps: Step 1: Determine the formation porosity; Step 2: Calculate the theoretical water line; Step 3: Calculate the theoretical oil line; Step 4: Quickly and qualitatively identify water - flooded layers; Step 5: Establish a water - flooding level identification chart; In Step 1, the specific steps for determining the formation porosity are as follows: Obtained by calculating using theoretical formulas and core - calibrated logging regression formulas through the three - porosity logging curves of conventional logging data, or obtained using nuclear magnetic resonance logging data; In Step 2, the specific steps for calculating the theoretical water line are as follows: Select a water layer section with relatively pure lithology, no calcite, and low shale content, draw a cross - plot of carbon - oxygen ratio vs. silicon - calcium ratio, find the best water line, regress to obtain the slope and intercept of the water line, and calculate the water line value at any depth point by combining the silicon - calcium ratio curve with the regressed slope and intercept; In Step 3, the specific steps for calculating the theoretical oil line are as follows: The difference between the oil line and the water line is expressed as 0.6×POR through porosity. 1.11 , then the oil line value at any depth point is calculated from the porosity and water line value at the corresponding depth point, and the formula is: COO = COW + △C / O; In Step 4, the specific steps for quickly and qualitatively identifying water - flooded layers are as follows: Conduct curve comparison, put the oil line, water line, and carbon - oxygen ratio curve in the same track and display them with the same scale; When the formation is not water - flooded, the C / O curve and the COO curve basically coincide and deviate far from the COW curve; When the formation is water - flooded, the C / O curve and the COO curve deviate. The degree of deviation is related to the water - flooding degree. The more serious the water - flooding, the farther the C / O curve and the COO curve deviate from each other and the closer the C / O curve is to the COW curve; In Step 5, the specific steps for establishing the water - flooding level identification chart are as follows: S1: Calculate the water - flooding level identification factors X and Y: The identification factor X is defined as the difference between the C / O curve and the COW curve, and the identification factor Y is defined as the difference between the COO curve and the C / O curve. Read the COO curve, COW curve, and C / O curve corresponding to different water - flooding levels according to the test data, and calculate the identification factors; S2: Use production dynamic data and water - plugging effect to analyze the water - flooding level of perforated intervals, and make a water - flooding level identification chart in combination with the water - flooding level identification factors in S1.

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