Heavy oil reservoir fluid property identification method based on formation resistivity correction

Abstract

The invention discloses a thickened oil reservoir fluid property identification method based on formation resistivity correction, and relates to the technical field of reservoir fluid identification, and the method comprises the following steps: obtaining a crude oil viscosity characterization index TPI; performing rock physical experiment oil analysis on the well core to obtain crude oil viscosity mu0 and crude oil density rho0 of a test oil layer; based on the crude oil viscosity characterization index TPI and the crude oil viscosity, establishing a TPI-viscosity relation model; establishing a viscosity and resistivity relation model; determining a resistivity correction coefficient; based on the correction coefficient L, the formation resistivity is determined, and the porosity resistivity chart is updated. According to the method, on the basis of conventional logging information, the logging curve data, geochemical pyrolysis parameters, rock physical experiments and oil testing input and production data are combined, the influence of the physical properties of the thickened oil on the resistivity is researched, the precision of recognizing the thickened oil layer through the resistivity-porosity intersection chart is effectively improved, the technical problem that the thickened oil reservoir is difficult to recognize is solved, and the method is suitable for popularization and application. And the interpretation coincidence rate of the region is improved in actual production application.

Description

Technical Field

[0001] The invention relates to the technical field of reservoir fluid identification, and in particular to a method for identifying the properties of heavy oil reservoir fluid based on formation resistivity correction. Background Art

[0002] In recent years, with the deepening of exploration, many reservoirs have been found that are interpreted as oil layers due to the heavy oil quality and high electrical properties of the reservoirs, but the oil test results do not match. This type of oil reservoir has attracted widespread attention in the oil industry. Heavy oil is a widely distributed energy source with huge resources. With the advancement of development technology, heavy oil has gradually become another main battlefield for oil development. Heavy oil is usually rich in organic matter, such as asphalt, wax, etc.; the content of different active components in heavy oil, such as aromatics, saturated hydrocarbons, etc. The presence of these active components affects the fluidity of heavy oil, making data interpretation complicated. A single logging curve often cannot provide enough information to accurately describe the properties of heavy oil fluids. However, due to the special physical properties of heavy oil and the limitations of current measurement technology, logging identification and interpretation of heavy oil layers is still a difficult problem.

[0003] At present, the commonly used identification methods are mainly various charts established by combining logging and oil testing data. The resistivity-porosity intersection diagram method is a kind of resistivity logging method. It is a commonly used fluid interpretation technology and also a graphical form of Archie's formula. Its application can vividly and intuitively distinguish oil, gas and water layers. However, for heavy oil layers, due to the influence of oil quality on resistivity, when using this chart for fluid identification, the oil testing conclusion is inconsistent with the interpretation conclusion, which affects the accuracy of fluid identification.

[0004] Therefore, for the fluid identification of heavy oil layers, it is urgent to propose a method for identifying the fluid properties of heavy oil reservoirs that is simple in logic, accurate and reliable. Summary of the invention

[0005] In order to solve the above technical problems, the present invention discloses a method for identifying fluid properties of heavy oil reservoirs based on formation resistivity correction. The method is based on conventional well logging data, combined with logging curve data, geochemical pyrolysis parameters, rock physics experiments and oil test production data, to study the influence of the physical properties of heavy oil on resistivity, effectively improves the accuracy of identifying heavy oil layers by resistivity-porosity intersection chart, and solves the technical problem of difficulty in identifying heavy oil reservoirs.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for identifying fluid properties of heavy oil reservoirs based on formation resistivity correction comprises the following steps:

[0008] Step 1, obtaining crude oil viscosity characterization index TPI;

[0009] Step 2: Perform rock physics experimental oil analysis on the well core to obtain the crude oil viscosity μ0 and crude oil density ρ0 of the test oil layer;

[0010] Step 3, based on crude oil viscosity characterization index TPI and crude oil viscosity, a TPI-viscosity relationship model is established;

[0011] Step 4, establishing a viscosity-resistivity relationship model;

[0012] Step 5, determine the resistivity correction factor;

[0013] Step 6: Based on the correction factor L, determine the formation resistivity and update the porosity resistivity map.

[0014] Optionally, in step 1, the calculation formula for the total hydrocarbon content in the geochemical pyrolysis process is:

[0015] S T =S0+S1+S2(1)

[0016] Where S0 is the free hydrocarbon content detected during geochemical pyrolysis, mg / g; S1 is the liquid hydrocarbon content detected during geochemical pyrolysis, mg / g; S2 is the pyrolysis hydrocarbon content detected during geochemical pyrolysis, mg / g; S T is the total hydrocarbon content during geochemical pyrolysis;

[0017] The calculation formula of crude oil viscosity index TPI is:

[0018] TPI=(S0+S1) / S T (2).

[0019] Optionally, in step 3, the TPI-viscosity relationship model is divided into the following types according to the porosity:

[0020] (1) When the porosity is less than 25%, there is a linear relationship between the crude oil viscosity index TPI and the viscosity, and the relationship is:

[0021] μ0=-21974×TPI+7297.6(3)

[0022] (2) When the porosity is greater than 25%, the crude oil viscosity index TPI has a relationship with the viscosity:

[0023] μ0=117.66×TPI -2.95 (4).

[0024] Optionally, in step 4, the viscosity and resistivity RT relationship model includes:

[0025] (1) When the viscosity μ0 < 2500, the effect of crude oil viscosity on resistivity is considered to be 0;

[0026] (2) When the viscosity μ0 ≥ 2500, the linear relationship between resistivity and viscosity is:

[0027]

[0028] Optionally, in step 5, the step of determining the resistivity correction coefficient specifically includes:

[0029] First, calculate the resistivity value RT0 corresponding to the viscosity of 2500; then calculate the resistivity value RT1 corresponding to the viscosity obtained by the TPI-viscosity relationship model. The resistivity correction coefficient L is expressed as:

[0030] L=RT1-RT0(6).

[0031] Optionally, in step 6, the corrected resistivity is:

[0032] RT=RT2-L(7)

[0033] Where RT2 is the true resistivity measured by the logging tool.

[0034] The beneficial effects of the present invention are:

[0035] (1) In order to solve the problem that heavy oil layers are difficult to interpret due to the physical properties of crude oil, the present invention is simple, effective, accurate, efficient and has good application effects.

[0036] (2) The present invention is very novel and uniquely adopts viscosity to correct resistivity, which greatly improves the accuracy of fluid identification in heavy oil layers and solves the problem of low consistency of logging interpretation in heavy oil layers.

[0037] (3) The present invention overcomes the shortcomings of the traditional resistivity-porosity intersection chart, takes the change of crude oil viscosity into consideration, and is more accurate in fluid identification for heavy oil layers than traditional fluid identification methods. The accuracy of fluid identification can be increased to 80%-95%. Compared with new and expensive fluid identification technologies, the cost can be reduced by about 60%, and the application effect and application value are better. With the improvement of the accuracy of heavy oil fluid identification, the recovery rate of the oil reservoir is also significantly enhanced. The improved logging fluid identification method can be applied to heavy oil layers in a targeted manner, and the fine identification of fluid types can be used to identify the fluid type. The invention lays the foundation for reservoir evaluation, geological modeling and numerical simulation. The method for identifying the properties of heavy oil reservoir fluids based on formation resistivity correction provides targeted ideas and methods for the oil-water interpretation of heavy oil reservoirs. The corrected resistivity and porosity are used as intersection charts to significantly improve the identification ability of heavy oil layer fluids in actual well logging interpretation, and solves the difficulties in well logging interpretation and evaluation. The invention has the advantages of simple logic, accuracy, reliability, strong targeting, etc., meets production needs, and has high practical value and promotion value in technical fields such as well logging interpretation and reservoir fluid identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a flow chart of the method for identifying fluid properties of heavy oil reservoirs based on formation resistivity correction of the present invention;

[0039] Figure 2 is the fluid viscosity-TPI model of the present invention;

[0040] Figure 3 is the viscosity-resistivity model of the present invention;

[0041] Figure 4 This is a resistivity and porosity fluid identification chart before correction in an embodiment of the present invention;

[0042] Figure 5 The corrected resistivity and porosity fluid identification chart of the embodiment of the present invention;

[0043] Figure 6 This is a well logging curve diagram of layer No. 15 in Well A according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the invention claimed for protection, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0045] A method for identifying fluid properties in heavy oil reservoirs based on formation resistivity correction, such as Figure 1 As shown, the following steps are included:

[0046] Step 1, obtaining crude oil viscosity characterization index TPI;

[0047] The geochemical pyrolysis data of the collection wells can be used to analyze the distillation properties of different components in heavy oil. Through geochemical pyrolysis experiments, components with different boiling points in crude oil, such as heavy hydrocarbons, wax, asphalt, etc., can be determined. The presence and content of these components can affect the viscosity and fluidity of crude oil. TPI reflects the ratio of gaseous hydrocarbons and liquid hydrocarbons to total hydrocarbons, which highlights the characteristics of the oil and gas layer and can reflect the weight of the oil.

[0048] The calculation formula for the total hydrocarbon content in the geochemical pyrolysis process is:

[0049] S T =S0+S1+S2(1)

[0050] Where S0 is the free hydrocarbon content detected during geochemical pyrolysis, mg / g; S1 is the liquid hydrocarbon content detected during geochemical pyrolysis, mg / g; S2 is the pyrolysis hydrocarbon content detected during geochemical pyrolysis, mg / g; S T is the total hydrocarbon content during geochemical pyrolysis;

[0051] The calculation formula for TPI, which reflects the ratio of gaseous hydrocarbons and liquid hydrocarbons to total hydrocarbons, is:

[0052] TPI=(S0+S1) / S T (2).

[0053] Step 2: Perform rock physics experimental oil analysis on the well core to obtain the crude oil viscosity μ0 and crude oil density ρ0 of the test oil layer;

[0054] Under laboratory control conditions, use a viscometer or a rotary viscometer to measure the actual viscosity of the fluid sample. Through testing under different temperature, shear rate and pressure conditions, the dynamic viscosity and static viscosity of the fluid can be obtained. This method uses the viscosity data μ0 of crude oil reaction at a temperature of 50°C.

[0055] Step 3: Based on the crude oil viscosity index TPI and crude oil viscosity, a TPI-viscosity relationship model is established, such as Figure 2 As shown in the figure, the smaller the TPI, the greater the viscosity and the thicker the crude oil. The TPI-viscosity relationship model is divided into the following types according to the porosity:

[0056] (1) When the porosity is less than 25%, there is a linear relationship between the crude oil viscosity index TPI and the viscosity, and the relationship is:

[0057] μ0=-21974×TPI+7297.6(3)

[0058] (2) When the porosity is greater than 25%, the crude oil viscosity index TPI has a relationship with the viscosity:

[0059] μ0=117.66×TPI -2.95 (4).

[0060] Step 4, establishing a viscosity-resistivity relationship model;

[0061] The high viscosity and complex chemical composition of heavy oil will affect the conduction of current, resulting in an increase in resistivity. The logging curve data of the test oil production layer and the crude oil viscosity obtained by oil analysis are used to establish a cross plot, and a viscosity-resistivity RT relationship model is established, such as Figure 3 As shown below:

[0062] (1) When the viscosity μ0<2500, the effect of crude oil viscosity on resistivity is considered to be 0, and the reservoir resistivity is more affected by the mud and pore structure of the region;

[0063] (2) When the viscosity μ0 ≥ 2500, the linear relationship between resistivity and viscosity is:

[0064]

[0065] Step 5, determine the resistivity correction factor;

[0066] Specifically include:

[0067] First, calculate the resistivity value RT0 corresponding to the viscosity of 2500; then calculate the resistivity value RT1 corresponding to the viscosity obtained by the TPI-viscosity relationship model. The resistivity correction coefficient L is expressed as:

[0068] L=RT1-RT0(6).

[0069] Step 6: Based on the correction factor L, determine the formation resistivity and update the porosity resistivity chart;

[0070] The corrected resistivity is:

[0071] RT=RT2-L(7)

[0072] Where RT2 is the true resistivity measured by the logging instrument; fluid identification is performed based on the cross-plot formed by the resistivity RT and porosity corrected by the evaluation model based on viscosity influence and containing a correction coefficient, which effectively improves the accuracy of logging fluid identification in heavy oil layers.

[0073] The embodiment of the present invention takes the reservoir of the unconsolidated sandstone depth section (height 77-14X 15 layer) of Well A in a certain oil field in China as an example, the resistivity RT2 of this layer is 11.3Ω, and the porosity φ is 31.9%. On the basis of the viscosity characterization by geochemical pyrolysis data, the specific implementation method of the viscosity correction method based on resistivity combined with the well logging curve data to improve the accuracy of the resistivity porosity fluid identification chart is as follows:

[0074] Step 1: Calculate the total hydrocarbon content S in the geochemical pyrolysis process based on the free hydrocarbon content S0, liquid hydrocarbon content S1, and pyrolysis hydrocarbon content S2 in the geochemical pyrolysis data of the test wells in the Baoqing Sag area. T , reflecting the oil and gas abundance of the reservoir. Calculate the total hydrocarbon content of the reservoir during geochemical pyrolysis:

[0075] S T =S0+S1+S2

[0076] Step 2: Calculate the reservoir crude oil viscosity characterization index TPI, which can reflect the ratio of gaseous hydrocarbons and liquid hydrocarbons to total hydrocarbons, highlight the characteristics of the oil and gas layer, and reflect the weight of the oil:

[0077] TPI=(S0+S1) / S T =0.3

[0078] Step 3: According to the crude oil viscosity characterization index TPI and viscosity relationship μ0 = 117.66 × TPI -2.95 , calculate the viscosity of the reservoir:

[0079] μ0=117.66*TPI^(-2.95)=5332

[0080] Step 4: Determine the correction coefficient: (1) When the viscosity μ0 = 2500, according to the relationship model formula between viscosity and resistivity:

[0081] RT0=3.562*e^(0.0002*μ0)=5.87Ω

[0082] (2) When the viscosity μ0 = 5332, according to the relationship model formula between viscosity and resistivity:

[0083] RT1=3.562*e^(0.0002*5332)=10.32Ω

[0084] (3) The correction coefficient L is:

[0085] L=RT1-RT0=10.32Ω-5.87Ω=4.45Ω

[0086] Step 5: Obtain the corrected resistivity RT:

[0087] RT=RT2-ΔRT=11.3Ω-4.45Ω=6.85Ω

[0088] According to geochemical pyrolysis data, the TPI of the reservoir is <0.35. Through viscosity and TPI model calculation, it is known that the average viscosity of the crude oil in this layer is large, μ0=5332, and the fluid property is heavy and viscous oil. When the reservoir properties are stable, the formation resistivity increases, resulting in inconsistency between the logging interpretation and the oil test conclusion.

[0089] Figure 4 This is the resistivity and porosity fluid identification plate of the example 77-14X 15 layer before correction. Figure 6 The logging curve of the reservoir is shown in the figure. The logging response characteristics of the reservoir are as follows: the natural gamma value of the reservoir is about 60 API, the resistivity is about 11 ohms, the envelope area of ​​the array induction resistivity curve and the natural gamma curve is large, and the reservoir data point is projected on Figure 4 The interpretation conclusion that the reservoir is an oil layer can be obtained from the fine lithology porosity-resistivity cross-plot of the Dongying Formation. Figure 5 For example, the intersection of resistivity and porosity after resistivity-based logging correction was performed on the 77-14X15 layer using the method of the present invention, and projected onto the fluid identification plate. The fluid properties of the reservoir were determined according to the regional position of the projection point on the fluid identification plate. Obviously, the interpretation conclusion of the reservoir should be that oil and water are in the same layer. After correction using the method of the present invention, the well was put into production for oil test. The daily oil production was 31.9 and the daily water production was 3.96. The oil test conclusion was that oil and water were in the same layer. The core physical experimental oil analysis of the crude oil obtained by production found that under the temperature condition of 50°C, the viscosity of the crude oil was 5286, which was basically consistent with the viscosity of 5332 calculated by the viscosity characterization index TPI. This example fully illustrates that the method of the present invention improves the fluid identification accuracy of the heavy oil reservoir in the region, improves the logging interpretation compliance rate, and solves the problem of low logging interpretation compliance rate of the heavy oil layer.

[0090] In order to verify the effectiveness of the method of the present invention, this embodiment combines the corrected plate with the logging results, and verifies the wells with oil test data in the study area. By consulting the well's stratum logging curve information, the fluid properties of the reservoir are determined by resistivity and porosity data, and the corresponding oil layer, water layer, oil-water layer, etc. are identified; finally, the fluid identification interpretation conclusion after the fluid property identification method based on formation resistivity viscosity correction is compared with the oil test conclusion, thereby verifying the reliability of the present invention. The results show that the plate can effectively identify the fluid in the study area and improve the accuracy of fluid identification in the area. Heavy oil refers to a type of crude oil with a higher viscosity than conventional crude oil. Therefore, the fluid identification method of correcting the formation resistivity according to the viscosity characteristics of heavy oil is very important for the oil industry because it directly affects the selection of mining and processing technology.

[0091] According to the characteristics of heavy oil in the Baoqing Sag area, the geochemical pyrolysis data were combined with the viscosity data of core physical experiments to establish an empirical relationship model suitable for this area. The relationship between viscosity and resistivity was established by combining the logging curves with the test oil production results. On this basis, viscosity correction was performed. Through the viscosity correction of resistivity, the resistivity-porosity fluid identification chart was improved, and the logging interpretation conformity rate in this area was improved.

[0092] It has been verified that the method of the present invention has the following advantages:

[0093] (1) Accurate fluid characterization: By considering the effect of viscosity on resistivity and starting from geochemical pyrolysis data, a viscosity characterization index is established, which provides a more accurate understanding and quantitative standard for the fluid properties of heavy oil reservoirs.

[0094] (2) This method can comprehensively analyze the impact of fluid viscosity changes on resistivity, and then enhance the ability of reservoir evaluation and production decision-making through resistivity-based viscosity correction.

[0095] (3) Cost-effective and non-invasive: This method utilizes existing logging technology, reducing the need for additional expensive equipment or invasive procedures.

[0096] (4) Real-time monitoring and optimization: The viscosity correction model is used for correction, which is more flexible and efficient, greatly facilitating the identification of fluid properties in difficult layers in the area. In actual production applications, it helps to adjust production strategies in a timely manner and optimize reservoir evaluation.

[0097] The method of the present invention aims at the difficult problem of identifying fluid in heavy oil logging. It establishes a crude oil viscosity characterization index based on geochemical pyrolysis data and core experimental oil analysis data, uses the relationship between crude oil viscosity and geochemical pyrolysis parameters to perform resistivity logging correction, and establishes a corrected resistivity and porosity intersection diagram, which significantly improves the identification ability of heavy oil reservoirs in actual logging interpretation. After testing a new well, the logging interpretation compliance rate is significantly improved. The method of the present invention can quickly and effectively improve the resistivity-porosity intersection diagram for heavy oil reservoirs, and combined with oil test and production data, improves the recognition rate of high-resistivity oil-water layers caused by excessive crude oil viscosity, solves the difficulties in logging interpretation and evaluation of heavy oil reservoirs, and meets actual production needs. The method of the present invention has the advantages of simple logic, accuracy and reliability. It has high practical value and promotion value in the field of fluid identification technology for heavy oil reservoirs in the Baoqing Depression area, and meets production needs.

[0098] Of course, the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by technicians in this technical field within the essential scope of the present invention should also fall within the protection scope of the present invention.

Claims

1. A method for identifying fluid properties of heavy oil reservoirs based on formation resistivity correction, characterized in that: The steps include: Step 1, obtaining crude oil viscosity characterization index TPI; Step 2: Perform rock physics experimental oil analysis on the well core to obtain the crude oil viscosity μ0 and crude oil density ρ0 of the test oil layer; Step 3, based on crude oil viscosity characterization index TPI and crude oil viscosity, a TPI-viscosity relationship model is established; Step 4, establishing a viscosity-resistivity relationship model; Step 5, determine the resistivity correction factor; Step 6: Based on the correction factor L, determine the formation resistivity and update the porosity resistivity map.

2. A method for identifying fluid properties of heavy oil reservoirs based on formation resistivity correction according to claim 1, characterized in that: In step 1, the calculation formula for the total hydrocarbon content during geochemical pyrolysis is: S T =S0+S1+S2(1) Where S0 is the free hydrocarbon content detected during geochemical pyrolysis, mg / g; S1 is the liquid hydrocarbon content detected during geochemical pyrolysis, mg / g; S2 is the pyrolysis hydrocarbon content detected during geochemical pyrolysis, mg / g; S T is the total hydrocarbon content during geochemical pyrolysis; The calculation formula of crude oil viscosity index TPI is: TPI=(S0+S1) / S T (2)。 3. A method for identifying fluid properties of heavy oil reservoirs based on formation resistivity correction according to claim 2, characterized in that: In step 3, the TPI-viscosity relationship model is divided into: (1) When the porosity is less than 25%, there is a linear relationship between the crude oil viscosity index TPI and the viscosity, and the relationship is: μ0=-21974×TPI+7297.6(3) (2) When the porosity is greater than 25%, the crude oil viscosity index TPI has a relationship with the viscosity: μ0=117.66×TPI -2.95 (4)。 4. A method for identifying fluid properties of heavy oil reservoirs based on formation resistivity correction according to claim 3, characterized in that: In step 4, the viscosity and resistivity RT relationship model includes: (1) When the viscosity μ0 < 2500, the effect of crude oil viscosity on resistivity is considered to be 0; (2) When the viscosity μ0 ≥ 2500, the linear relationship between resistivity and viscosity is:

5. A method for identifying fluid properties of heavy oil reservoirs based on formation resistivity correction according to claim 4, characterized in that: In step 5, the step of determining the resistivity correction coefficient specifically includes: First, calculate the resistivity value RT0 corresponding to the viscosity of 2500; then calculate the resistivity value RT1 corresponding to the viscosity obtained by the TPI-viscosity relationship model. The resistivity correction coefficient L is expressed as: L=RT1-RT0(6).

6. A method for identifying fluid properties of heavy oil reservoirs based on formation resistivity correction according to claim 5, characterized in that: In step 6, the corrected resistivity is: RT=RT2-L(7) Where RT2 is the true resistivity measured by the logging tool.

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