A method for identifying reservoirs free from the effects of residual oil

Abstract

The application discloses a reservoir identification method for removing residual oil influence, and belongs to the field of reservoir evaluation. The application establishes a residual oil quantitative characterization index from the logging response difference between a conventional oil reservoir and a high-resistance water layer, forms a resistivity correction chart by using a relationship between the resistivity of the regional water layer and the residual oil index, and makes a crossplot chart by using the corrected resistivity and the acoustic travel time, so that the identification ability for the high-resistance water layer is obviously improved in actual logging interpretation. Through new well testing, the coincidence rate of logging interpretation is obviously improved. The application can quickly and effectively identify the high-resistance water layer influenced by residual oil, solves the logging interpretation and evaluation difficulty, and meets the production demand.

Description

Technical Field

[0001] This invention belongs to the field of reservoir evaluation, and in particular to a reservoir identification method that removes the influence of residual oil. Background Technology

[0002] For oil-water identification in low-contrast oil reservoirs, common evaluation methods include the surrounding rock resistivity ratio method, cross-plotting method, multi-parameter pattern recognition method, and nuclear magnetic resonance differential spectroscopy (NMR) method. The surrounding rock resistivity ratio and sonic transit time cross-plotting method uses the resistivity of the target layer, the ratio of the resistivity of the surrounding rocks above and below, and the sonic transit time of the target layer to create an oil-water identification chart. However, the resistivity values ​​of the surrounding rocks above and below the reservoir are generally unstable. The multi-parameter pattern recognition method uses mathematical discrimination to classify reservoir types and identify fluids from multiple logging curves or interpretation results curves, but it does not consider whether there is a geologically significant correlation between the logging curves involved in the pattern recognition and the fluid type. These two conventional logging identification methods do not address the influence of high water-resistivity layers, thus failing to identify them and resulting in low logging interpretation accuracy. Furthermore, NMR differential spectroscopy has limitations in oil-water identification in high-porosity or oleophilic reservoirs, as differential spectral signals also exist in high-porosity water layers or oleophilic reservoirs. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art and provide a reservoir identification method that removes the influence of residual oil.

[0004] To achieve the above objectives, the present invention employs the following technical solution:

[0005] A reservoir identification method that removes the influence of residual oil includes the following steps:

[0006] Step 1: Obtain the porosity logging curve, calculate the envelope area between the compensated neutron curve and the core density curve, and calculate the average value of the envelope area of ​​each layer in turn.

[0007] Step 2: The average value of the envelope area of ​​each layer is taken as the residual oil index (OI) of each layer;

[0008] Based on the results of oil testing in multiple wells that have produced water, the resistivity R of each layer is obtained.

[0009] Through numerical fitting, an exponential function relationship between the water layer resistivity R and the residual oil index OI was established:

[0010] R = A × e B×OI (1)

[0011] In the formula: A and B are both constant coefficients in the exponential relationship;

[0012] When the residual oil index OI is 0, this corresponds to the baseline value of water layer resistivity R. blWhen the residual oil index OI is not 0, the resistivity correction ΔR is as follows:

[0013] ΔR=A×e B×OI -R bl (2)

[0014] The resistivity after eliminating the influence of residual oil is:

[0015] R c =RLLd-(A×e B×OI -R bl (3)

[0016] Where: R is the fitted water layer resistivity, Ω·m; OI is the residual oil index, decimal; R bl RL is the baseline resistivity of the water layer, i.e., the resistivity of the water layer when the residual oil index is 0, in Ω.m; ΔR is the resistivity correction amount in Ω.m; RLLd is the deep lateral resistivity in Ω.m; R c To remove residual oil that could affect the corrected resistivity;

[0017] Step 3: Obtain logging curves with oil testing results. The logging curves include logging curves for oil-bearing layers, oil-water co-layers, poor oil-bearing layers, oil-bearing water layers, and water layers.

[0018] The resistivity of each layer is corrected according to steps (1)-(2) to obtain the corrected resistivity;

[0019] Obtain the acoustic transit time curve for each layer and calculate the corresponding acoustic transit time characteristic value;

[0020] The acoustic transit time characteristic values ​​and corrected resistivity of each layer are projected onto the cross-plot of acoustic transit time characteristic values ​​and corrected resistivity to form a fluid identification plot.

[0021] Step 4: Obtain the logging curves of the reservoir to be identified;

[0022] The resistivity of the layer to be identified is corrected according to steps (1) and (2) to obtain the corrected resistivity.

[0023] The corrected resistivity and acoustic transit time characteristic values ​​corresponding to the layer are projected onto the fluid identification chart, and the fluid properties of the reservoir are determined based on the regional location of the projection point on the fluid identification chart.

[0024] Furthermore, the specific steps in step one are as follows:

[0025] The range of values ​​for both is determined by the intersection of the compensated neutron curve and the core density curve.

[0026] The compensated neutron curve and core density curve within the range of values ​​are normalized.

[0027] Calculate the envelope area on either side of the compensated neutron curve, and calculate the envelope area on the corresponding side of the core density curve. The difference between the two envelope areas is the envelope area between the compensated neutron curve and the core density curve.

[0028] Furthermore, the range of values ​​for the compensated neutron curve is [CNL]. L CNL R ] = [-10, 40], the value range of the core density curve is [DEN] L DEN R = [2.2, 2.8].

[0029] Furthermore, the envelope area of ​​the core density logging curve is:

[0030]

[0031] In the formula, DEN is the core density, in g / cm³. 3 DEN_area, core density envelope area, dimensionless; DEP_min, reservoir initiation depth, m; DEP_max, reservoir termination depth, m.

[0032] Furthermore, the envelope area of ​​the compensated neutron logging curve is calculated:

[0033]

[0034] In the formula, CNL represents the compensating neutron, %; CNL_area represents the envelope area of ​​the compensating neutron, dimensionless.

[0035] Furthermore, the average envelope area of ​​the reservoir compensated neutron and density logging curves is:

[0036]

[0037] In the formula, OI is the residual oil index, a decimal; DEP_min is the reservoir initiation depth, in meters; and DEP_max is the reservoir termination depth, in meters.

[0038] Furthermore, step three also includes: dividing the fluid identification map according to the reservoir type distribution.

[0039] Furthermore, the fluid identification map is divided into an oil layer region, an oil-water co-layer region, and an oil-water layer and a water layer region.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] The reservoir identification method of this invention, which removes the influence of residual oil, establishes a quantitative characterization index for residual oil based on the difference in logging responses between conventional oil layers and high-resistivity water-producing layers. A resistivity correction chart is generated using the relationship between the resistivity of the water layer and the residual oil index in this area. A cross-plot is then created using the corrected resistivity and sonic transit time. This significantly improves the ability to identify high-resistivity water layers in actual well logging interpretation. New well testing shows a significant improvement in the accuracy of well logging interpretation. This invention can quickly and effectively identify high-resistivity water layers affected by residual oil, solving the difficulties in well logging interpretation and evaluation, and meeting production needs. Attached Figure Description

[0042] Figure 1 Flowchart for an embodiment;

[0043] Figure 2 To correct the resistivity of the chart by removing residual oil;

[0044] Figure 3 This is a cross-plot of the corrected resistivity versus acoustic time difference.

[0045] Figure 4 A diagram illustrating the evaluation results of a high water-resistant layer. Detailed Implementation

[0046] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0047] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0048] The present invention will now be described in further detail with reference to the accompanying drawings:

[0049] See Figure 1 , Figure 1The flowchart below illustrates an embodiment of the present invention, which provides a reservoir identification method to remove the influence of residual oil, comprising the following steps:

[0050] Step 1: Calculate the compensation neutrons and core density in channel 4 of the graph (e.g., ...). Figure 4 As shown), the left and right scales of the fixed compensated neutron and core density logging curves are used, and the two curves adopt linear scales. The compensated neutron scale range is [CNL]. L CNL R ] = [-10, 40], core density scale range is [DEN] L DEN R = [2.2, 2.8].

[0051] Step two: First, use the normalization method to eliminate the difference between the compensated neutron and the core density curve due to their different order of magnitude. Calculate the area of ​​the leftward envelope of the core density curve and then calculate the area of ​​the leftward envelope of the compensated neutron. The difference between the two envelope areas is the envelope area of ​​the reservoir compensated neutron and the core density. Finally, calculate the average value of the envelope areas.

[0052] Calculate the leftward envelope area of ​​the core density logging curve:

[0053]

[0054] In the formula, DEN is the core density, in g / cm³. 3 DEN_area, the leftward envelope area of ​​the core density, dimensionless; DEP_min, the initial depth of the reservoir, m; DEP_max, the final depth of the reservoir, m.

[0055] Calculate the leftward envelope area of ​​the compensated neutron logging curve:

[0056]

[0057] In the formula, DEN is the core density, %; CNL_area is the compensated left envelope area, dimensionless.

[0058] The average envelope area of ​​the final reservoir compensated neutron and density logging curves is:

[0059]

[0060] In the formula, HRO residual oil index is a decimal; DEP_min is the reservoir initiation depth in m; DEP_max is the reservoir termination depth in m; and BC is the sampling interval of the logging curve, 0.125 in m.

[0061] Step 3: Based on the results of oil testing at multiple wells in the study area, obtain resistivity correction charts to remove the influence of residual oil, such as... Figure 2As shown, the resistivity is extracted and the residual oil index OI is calculated to establish an exponential function relationship between the water layer resistivity R and the residual oil index OI:

[0062] R = A × e B×OI (1)

[0063] When the residual oil index (OI) is 0, it means that the reservoir is not affected by residual oil, and its effect on resistivity is also 0. The corresponding baseline value of water layer resistivity R is... bl The resistivity is 31.86 Ω·m. When the resistivity of the water layer is too high due to the influence of residual oil, the resistivity needs to be corrected to eliminate the influence of residual oil. The resistivity correction amount ΔR is as follows:

[0064] ΔR=A×e B×OI -R bl (2)

[0065] Finally, the resistivity correction formula to eliminate the influence of residual oil is obtained:

[0066] R c =RLLd-(A×e B×OI -R bl (3)

[0067] Where: R is the fitted water layer resistivity, Ω·m; OI is the residual oil index, decimal; R bl RL is the baseline resistivity of the water layer, i.e., the resistivity of the water layer when the residual oil index is 0, in Ω.m; ΔR is the resistivity correction amount in Ω.m; RLLd is the deep lateral resistivity in Ω.m; R c To remove residual oil that could affect the corrected resistivity.

[0068] Step four: Using data from all wells with oil testing results, including oil-bearing layers, oil-water co-containing layers, poor oil-bearing layers, oil-water-bearing layers, and water-bearing layers, extract the corrected resistivity and sonic transit time curves for each layer. Then, project the layer locations onto the cross-plot, as shown below. Figure 3 As shown, the area where the vertical line intersects with the upper broken line is the oil layer area, the area where the vertical line intersects with the upper and lower broken lines is the oil-water co-layer area, and the area below the lower broken line area is the oil-water layer and water layer area.

[0069] Step 5: Applying this to a specific well, first perform resistivity correction to remove residual oil in the new well, then project the corrected resistivity and sonic transit time characteristic values ​​corresponding to the formation onto the fluid identification chart, and determine the fluid properties of the reservoir based on the location of the projection point in the area of ​​the corrected resistivity and sonic transit time intersection chart.

[0070] In actual data processing, the residual oil resistivity correction method is implemented by writing a program to form a method module. Figure 4The image shows the logging interpretation results for well L1. The second and third tracks represent the resistivity of the array induction logging and the resistivity after residual oil removal correction, respectively. The fourth track represents the porosity logging series. The average resistivity of layer 28 in the well logging is 76.93 Ω·m, the average sonic transit time is 234.31 μs / m, the calculated porosity is 13.53%, and the permeability is 5.70 mD. This layer has good physical properties and high resistivity. According to the conventional well logging test chart analysis, the layer with a sonic transit time of 234.31 μs / m and a resistivity of 76.93 Ω·m is located at the boundary between the oil layer and the oil-water layer zone on the chart. It is easy to interpret this layer as an oil layer during the first interpretation of the well logging. From the envelope area of ​​the fourth compensated neutron and density curve, it can be seen that the resistivity of layer 28 is high due to the influence of residual oil. As shown in the third line, the corrected resistivity after removing the influence of residual oil is 61.91 Ω·m, which is about 15.02 Ω·m lower than the resistivity before correction. Cross-plot analysis of the corrected resistivity and sonic transit time shows that this layer clearly falls in the oil-water co-layer zone of the oil-water interpretation chart. The oil production at this layer was 1.11 tons per day, and the water production was 48.2 cubic meters per day. 3 The / d value indicates a typical oil-water co-containment layer, demonstrating that the interpretation of reservoir fluid properties using the corrected resistivity is consistent with the well testing results. This method can quickly and effectively identify high water-resistivity layers, improving the accuracy of well logging interpretation.

[0071] This invention first utilizes thin section, core analysis, logging data, and well testing data to analyze the impact of reservoir lithology, physical properties, formation water salinity, and rock wettability on reservoir resistivity, clarifying the main controlling factors for high-resistivity water-producing layers in this region. Then, based on the difference in logging responses between conventional oil layers and high-resistivity water-producing layers, a quantitative characterization index for residual oil is established. A resistivity correction chart is generated using the relationship between water layer resistivity and the residual oil index in this region. The corrected resistivity is then used to create a cross-plot with sonic transit time, significantly improving the ability to identify high-resistivity water layers in actual well logging interpretation. This invention is simple, highly scalable, and effectively avoids the low accuracy of well logging interpretation using the surrounding rock resistivity ratio method and pattern recognition method, as well as the limitations of fluid identification using nuclear magnetic resonance differential spectroscopy. It has good universality and promotional value.

[0072] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A reservoir identification method to remove the influence of residual oil, characterized in that, Includes the following steps: Step 1: Obtain the porosity logging curve, calculate the envelope area between the compensated neutron curve and the core density curve, and calculate the average value of the envelope area of ​​each layer in turn. Step 2: The average value of the envelope area of ​​each layer is used as the residual oil index of each layer. OI ; Based on the results of oil testing from multiple wells that produced water, the resistivity of each layer was obtained. ; The water layer resistivity was established through numerical fitting. With residual oil index Exponential function relationship: （1） In the formula: A , B All are constant coefficients; When residual oil index When it is 0, this corresponds to the baseline value of water layer resistivity. R bl When the residual oil index When it is not 0, the resistivity correction amount as follows: （2） The resistivity after eliminating the influence of residual oil is: （3） In the formula: The deep lateral resistivity is given in Ω·m. Step 3: Obtain logging curves with oil testing results. The logging curves include logging curves for oil-bearing layers, oil-water co-layers, poor oil-bearing layers, oil-bearing water layers, and water layers. The resistivity of each layer is corrected according to steps one and two to obtain the corrected resistivity. Extract the acoustic transit time curve for each layer and calculate the corresponding acoustic transit time characteristic value; The acoustic transit time characteristic values ​​and corrected resistivity of each layer are projected onto the cross-plot of acoustic transit time characteristic values ​​and corrected resistivity to form a fluid identification plot. Step 4: Obtain the logging curves of the reservoir to be identified; The resistivity of the layer to be identified is corrected according to steps one and two to obtain the corrected resistivity. The corrected resistivity and acoustic transit time characteristic values ​​corresponding to the layer are projected onto the fluid identification chart, and the fluid properties of the reservoir are determined according to the regional position of the projection point on the fluid identification chart. The range of values ​​for the compensated neutron curve is [ CNL L , CNL R The value range of the core density curve is [-10, 40]. DEN L , DEN R = [2.2, 2.8]; The envelope area of ​​the core density logging curve is: （4） In the formula, DEN is the core density, g / cm3; The reservoir initiation depth is in meters (m). The reservoir termination depth is in meters (m). Calculate the envelope area of ​​the compensated neutron logging curve: （5） In the formula, CNL To compensate for neutrons, % The average envelope area of ​​the reservoir compensated neutron and density logging curves is: （6）。 2. The reservoir identification method for removing the influence of residual oil according to claim 1, characterized in that, The specific steps for step one are as follows: The range of values ​​for both is determined by the intersection of the compensated neutron curve and the core density curve. The compensated neutron curve and core density curve within the range of values ​​are normalized. Calculate the envelope area on either side of the compensated neutron curve, and calculate the envelope area on the corresponding side of the core density curve. The difference between the two envelope areas is the envelope area between the compensated neutron curve and the core density curve.

3. The reservoir identification method for removing the influence of residual oil according to claim 1, characterized in that, Step three also includes: dividing the fluid identification map according to the reservoir type distribution.

4. The reservoir identification method for removing the influence of residual oil according to claim 3, characterized in that, The fluid identification map is divided into an oil layer region, an oil-water co-layer region, and an oil-water layer and a water layer region.

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