Geometric factor adaptive array resistivity curve correction method

Abstract

The present application relates to the technical field of well logging, and discloses a geometry factor adaptive array resistivity curve correction method, which comprises using resistivity data measured by array resistivity instrument in shallow detection and deep detection modes as estimated values of invasion zone resistivity and undisturbed formation resistivity, giving an invasion radius, calculating corresponding geometry factors, and obtaining theoretical resistivity data of different detection modes through an adaptive correction processing algorithm. The present application uses the geometry factor adaptive correction processing algorithm to calculate theoretical resistivity data of different radial detection depths as corrected resistivity data, which conforms to the ordering relationship of resistivity curves of different radial detection depths under the condition of mud invasion, effectively eliminates the resistivity disorder phenomenon caused by array resistivity measurement in complex well conditions, and thus provides more accurate resistivity information of different radial detection depths for well logging interpreters.

Description

Technical Field

[0001] This invention relates to the field of well logging technology, specifically to a geometric factor adaptive array resistivity curve correction method. Background Technology

[0002] Resistivity logging is a key parameter for evaluating the physical, electrical, and oil-bearing properties of underground reservoirs. Array resistivity logging tools can obtain resistivity information of reservoirs at different radial distances by working at different radial depths. The separation relationship of resistivity curves at different depths can be used to determine the permeability of the reservoir; the greater the separation, the better the permeability. At the same time, the properties of the fluids contained in the reservoir can be identified based on the resistivity value. The resistivity value of oil and gas layers is usually greater than that of water layers. Furthermore, the oil and gas saturation of the reservoir can be calculated by using the resistivity curve at the deepest depth.

[0003] Currently, mainstream array resistivity logging tools include array lateral and array induction logging tools, which can typically obtain resistivity curves for four to six radial depths of the reservoir. In actual logging operations, when array resistivity logging tools are used in permeable reservoirs, the resistivity measurement decreases with increasing depth when the mud has low resistivity invasion, and increases with increasing depth when the mud has high resistivity invasion. However, due to the influence of wellbore diameter, mud resistivity, non-uniform mud invasion, well temperature, layer thickness, and instrument eccentricity, the array resistivity curves may exhibit disorder, meaning the order of the resistivity curves does not conform to the radial depth variation relationship. This disordered array resistivity curve phenomenon can confuse logging interpreters and prevent accurate evaluation of reservoir parameters. Summary of the Invention

[0004] This invention provides a geometric factor adaptive array resistivity curve correction method, which has the beneficial effect of eliminating resistivity disorder in array resistivity measurement. It solves the problem mentioned in the background art that the disorder of array resistivity curves can cause confusion for well logging interpreters and make it impossible to accurately evaluate reservoir parameters.

[0005] This invention provides the following technical solution: a geometric factor adaptive array resistivity curve correction method, wherein the geometric factor adaptive array resistivity curve correction method includes the following steps:

[0006] Resistivity data actually measured using shallow and deep probe modes of an array resistivity instrument are used as estimates of resistivity in the intrusive zone and resistivity in the undisturbed formation.

[0007] Given the invasion radius r j Calculate the corresponding geometric factors Theoretical resistivity data for different detection modes are obtained through an adaptive correction processing algorithm.

[0008] The theoretical resistivity data is matched with the actual measured data, and the theoretically calculated resistivity data corresponding to the smallest difference between the two is used as the array resistivity data after geometric factor correction.

[0009] Through the geometric factors The corrected array resistivity data eliminates resistivity disorder in array resistivity measurements.

[0010] As an optional scheme of the geometric factor adaptive array resistivity curve correction method of the present invention, the geometric factor is a quantitative characterization parameter of the intrusion radius corresponding to different detection depths. The geometric factor is calculated by Nth-order polynomial fitting, with the intrusion radius as the independent variable and the geometric factor as the dependent variable. The calculation is completed by combining the polynomial fitting coefficients corresponding to each detection depth. The fitting coefficients are adjusted accordingly with different detection depths.

[0011] Wherein: the geometric factor It is obtained through Nth-order polynomial fitting, and the calculation formula is:

[0012] ;

[0013] in, These are the geometric factors corresponding to different detection depths;

[0014] i represents different detection depths;

[0015] a i0 ,a i1 ,…,a iN The coefficients are the fitting coefficients for an Nth-degree polynomial.

[0016] As an optional scheme of the geometric factor adaptive array resistivity curve correction method of the present invention, the estimated values ​​of the resistivity of the intrusive zone and the resistivity of the original formation are based on multiple sets of array resistivity curve data measured by the array resistivity instrument. The values ​​are obtained by weighting the curve data at different detection depths by setting corresponding weight factors. The weight factors can be adaptively adjusted according to the actual logging conditions.

[0017] Wherein: the resistivity R of the invasive band xo and the original formation resistivity R t The formula for calculating the estimated value is:

[0018] ;

[0019] Where α and β are weighting factors; M2R2, M2R9, M2R3 and M2RX are array resistivity curve data.

[0020] As an optional scheme of the geometric factor adaptive array resistivity curve correction method of the present invention, it also includes the step of calculating the value of the invasion radius and the subdivision of the geometric factor of multiple detection depths: the invasion radius is taken within a preset minimum and maximum value range, the minimum value is greater than the wellbore radius, and the maximum value is limited by the deepest detection depth of the array resistivity instrument, and the invasion radius gradually changes from the minimum value to the maximum value; for different target detection depths of the instrument, the corresponding polynomial fitting formula is used to calculate the geometric factor, and each detection depth is matched with a dedicated polynomial fitting coefficient, so that the geometric factor corresponding to different detection depths can be calculated independently for the same invasion radius.

[0021] This also includes:

[0022] ;

[0023] Where, r min r is the minimum value of the invasion radius. max This represents the maximum value of the invasion radius;

[0024] Given the invasion radius r j By r min Change to r max ;

[0025] By the given invasion radius r j Calculate the geometric factors corresponding to different target detection depths. The calculation formula is:

[0026] .

[0027] As an alternative scheme of the geometric factor adaptive array resistivity curve correction method described in this invention, theoretical array resistivity data at different radial detection depths are obtained by weighted calculation using the estimated resistivity of the intrusion zone, the estimated resistivity of the undisturbed formation, and the geometric factor of the intrusion radius corresponding to each detection depth as core calculation parameters, combined with the response principle of array resistivity logging. For each preset intrusion radius, a set of theoretical array resistivity data for the entire detection depth can be calculated.

[0028] Wherein: the theoretical array resistivity data for different radial probe depths is calculated using the following formula:

[0029] .

[0030] As an optional scheme of the geometric factor adaptive array resistivity curve correction method of the present invention, the minimum difference between the theoretical array resistivity data and the actual measured array resistivity data is quantitatively selected by calculating the Euclidean distance between the two data. A set of theoretical array resistivity data with full detection depth is integrated into a row vector, and the corresponding measured array resistivity data is integrated into another row vector. The Euclidean distance is calculated based on the two row vectors.

[0031] Wherein: the Euclidean distance L is calculated by comparing the theoretical array resistivity data with the actual measured array resistivity data. j By calculating the Euclidean distance L j To select the minimum difference between theoretical resistivity data and actual measured data;

[0032] Define the theoretical array resistivity data as a row vector:

[0033] ;

[0034] Define the actual measured array resistivity data as a row vector:

[0035] .

[0036] As an optional scheme of the geometric factor adaptive array resistivity curve correction method of the present invention, the Euclidean distance is the square root of the sum of the squares of the differences between the corresponding elements of two row vectors. For each intrusion radius within the range of values, the corresponding Euclidean distance is calculated once. The Euclidean distances corresponding to all intrusion radii are iteratively calculated and compared, and the intrusion radius corresponding to the minimum Euclidean distance is selected. The theoretical array resistivity data under this radius is the array resistivity data after geometric factor correction.

[0037] Wherein, the Euclidean distance L j The calculation formula is:

[0038] ;

[0039] in, The square root of the sum of the squares of the elements corresponding to the difference vector;

[0040] Circular intrusion radius r j ;

[0041] Where j = 1, 2, ..., m, the minimum Euclidean distance is taken, i.e., min(L j The theoretical array resistivity data corresponding to the obtained theoretical array resistivity data is used as the array resistivity data after geometric factor correction.

[0042] As an optional scheme of the geometric factor adaptive array resistivity curve correction method of the present invention, the corrected array resistivity data follows a forward or reverse order rule, that is, the greater the detection depth, the greater the resistivity value in the low-impact high-resistivity layer, and the smaller the resistivity value in the high-impact low-resistivity layer.

[0043] The present invention has the following beneficial effects:

[0044] 1. This geometric factor adaptive array resistivity curve correction method, based on array resistivity data collected by an array resistivity measuring instrument under different detection modes, calculates theoretical resistivity data for different radial detection depths using only the theoretical geometric factors corresponding to different radial detection depths of the array resistivity measuring instrument, without changing the instrument's mechanical structure and circuit design. This corrected resistivity data conforms to the sorting relationship of resistivity curves at different radial detection depths under mud invasion conditions, effectively eliminating the resistivity disorder phenomenon caused by the influence of array resistivity measurement in complex well conditions. This provides well logging interpreters with more accurate resistivity information at different radial detection depths, providing strong data support for the accurate evaluation of underground reservoirs.

[0045] 2. The geometric factor adaptive array resistivity curve correction method ensures that the corrected array resistivity curves are not out of order and conform to the response law of array resistivity under mud invasion conditions. This provides well logging data interpreters with more accurate resistivity information at different radial depths, and provides strong data support for reservoir fluid identification and fine evaluation. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the overall process of the present invention.

[0047] Figure 2 This is a schematic diagram of the adaptive correction steps for geometric factors in this invention.

[0048] Figure 3 This is a schematic diagram of the array resistivity measuring instrument of the present invention.

[0049] Figure 4 This is a schematic diagram of the stratigraphic model of the present invention.

[0050] Figure 5 This is a diagram of the array resistivity geometry factor of the present invention.

[0051] Figure 6 This is a graph showing the array resistivity before and after geometric factor correction according to the present invention. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0053] Example 1

[0054] Please see Figures 1-6 Furthermore, a geometric factor adaptive array resistivity curve correction method is disclosed, which includes matching theoretical geometric factor models with measured data, inverting the optimal intrusion radius through optimization methods, and thus obtaining a corrected resistivity curve that conforms to physical laws.

[0055] Specifically, the array resistivity measuring device consists of an instrument core, a transmitting coil T, shielding coils B1 to B6, and main receiving coils R1 to R6. All coils are coaxially arranged on the instrument core, with the shielding coil and receiving coil on the same side as the transmitting coil. The transmitting coil T, shielding coil B, and main receiving coil R form a three-coil system TBR. The instrument consists of six three-coil systems, with the distance from the transmitting coil increasing sequentially. This allows for the measurement of resistivity information at different radial depths of the formation. Through ground data processing, the six sets of original measurement information can be synthesized to obtain array resistivity curves at radial detection depths of 10, 20, 30, 60, 90, and 120 inches.

[0056] The stratigraphic model consists of two radial layers (intrusive zone and undisturbed strata) and an infinitely thick longitudinal strata. The instrument measurement response comes from the contribution of the surrounding strata. Therefore, the measurement response of the three-coil system at different source distances is the weighted sum of the contributions of each part of the strata. The deeper the probe, the greater the proportion of the measurement response from the undisturbed strata.

[0057] Resistivity data actually measured using shallow and deep probe modes of an array resistivity instrument are used as estimates of resistivity in the intrusive zone and resistivity in the undisturbed formation.

[0058] Given the invasion radius r j Calculate the corresponding geometric factors Theoretical resistivity data for different detection modes are obtained through an adaptive correction processing algorithm.

[0059] The graphs depict the geometric factors at different radial probe depths (10, 20, 30, 60, 90, and 120 inches) for the array resistivity instrument. The horizontal axis represents the intrusion radius, and the vertical axis represents the geometric factor. As the intrusion radius increases, the geometric factor also increases, indicating that the contribution of the intrusion zone to the instrument's measurement response becomes more significant. Nth-order polynomial fitting is performed on these six radial integral geometric factors, and the fitting formula is as follows:

[0060] ;

[0061] in, These are the geometric factors corresponding to different detection depths;

[0062] i represents different detection depths; a i0 ,a i1 ,…,a iN The coefficients are the fitting coefficients for an Nth-order polynomial.

[0063] The theoretical resistivity data is matched with the actual measured data, and the theoretically calculated resistivity data corresponding to the smallest difference between the two is used as the array resistivity data after geometric factor correction.

[0064] During its movement downhole, the measuring instrument acquired six array resistivity curves (M2R1, M2R2, M2R3, M2R6, M2R9, and M2RX, representing probe depths of 10, 20, 30, 60, 90, and 120 inches, respectively) at different depths. The resistivity in the shallow and deep measurement modes was used as the resistivity R of the intrusion zone. xo and the original formation resistivity R t The estimated value;

[0065] Wherein, the resistivity R of the invasive band xo and the original formation resistivity R t The formula for calculating the estimated value is:

[0066] ;

[0067] Where α and β are weighting factors;

[0068] M2R2, M2R9, M2R3, and M2RX are array resistivity curve data;

[0069] Also includes:

[0070] ;

[0071] Where, r min r is the minimum value of the invasion radius. max This represents the maximum value of the invasion radius;

[0072] The minimum value of the invasion radius is r. min A radius slightly larger than the wellbore radius is used (e.g., if the wellbore diameter is 8 inches, then a radius of 4 inches ≈ 0.1m). Considering that mud intrusion cannot be zero (even in dense layers there is slight filtration loss), r is generally set as... min ≈0.1-0.2m;

[0073] The maximum value of the invasion radius r max Limited by the deepest detection depth (the deepest in this case is 120 inches ≈ 3.05m);

[0074] It should be noted that if the value is set too large (e.g., close to 120 inches), the geometry factor will approach 1, resulting in a loss of distinguishability; if it is set too small, it will not be able to cover the actual intrusion situation.

[0075] Given the invasion radius r j By r min Change to r max The step size of the change is Δr, and r j The geometric factor Gr corresponding to different target detection depths was calculated respectively. i (r j );

[0076] By the given invasion radius r j Calculate the geometric factor Gr for different target detection depths. i (r), the calculation formula is:

[0077] ;

[0078] The theoretical array resistivity data are calculated at different radial probe depths using the following formula:

[0079] ;

[0080] The Euclidean distance L is calculated by comparing the theoretical array resistivity data with the actual measured array resistivity data. j By calculating the Euclidean distance L j To select the minimum difference between theoretical resistivity data and actual measured data;

[0081] Define the theoretical array resistivity data as a row vector:

[0082] ;

[0083] Define the actual measured array resistivity data as a row vector:

[0084] ;

[0085] Euclidean distance L j The calculation formula is:

[0086] ;

[0087] wherein, the square root of the sum of the squares of the elements corresponding to the difference vector;

[0088] the cyclic invasion radius r j ;

[0089] where j = 1, 2, …, m, take the minimum value of the corresponding Euclidean distance, that is, the theoretical array resistivity data corresponding to min(L j ), and use the obtained theoretical array resistivity data as the array resistivity data after geometric factor correction;

[0090] The measured array resistivity curve and the array resistivity curve after adaptive correction using the geometric factor are given. The first trace is the depth trace, the second trace is the actually measured array resistivity curve, and the third trace is the array resistivity curve after adaptive correction using the geometric factor. From the comparison results, it can be seen that the order of the corrected array resistivity curve is not disordered. Taking the measurement depth of 714.2 m as an example, the order of the measured array resistivity values is M2R3 < M2R6 < M2R9 < M2R1 < M2R2 < M2RX, and their values are 31.01, 35.56, 47.01, 56.62, 66.61, and 120.34 in sequence. The order of the array resistivity values after geometric factor correction is M^2R1S < M^2R2S < M^2R3S < M^2R6S < M^2R9S < M^2RXS, and their values are 32.11, 32.85, 33.92, 39.39, 46.9, and 53.34 in sequence. The corrected array resistivity data is in positive or reverse order, that is, the greater the detection depth, the greater the resistivity value in the low invasion and high resistivity layer, and the smaller the resistivity value in the high invasion and low resistivity layer, which conforms to the response law of the array resistivity in the case of low resistivity invasion of the mud, thus providing more accurate resistivity information of different radial detection depths for well logging data interpreters and providing strong data support for reservoir fluid identification and fine evaluation;

[0091] Therefore, in this embodiment, by establishing a longitudinally infinitely thick formation model, the contribution rate of a cylinder with a certain radial radius to the measuring instrument is defined as the geometric factor of the array resistivity logging instrument. Then, the contribution of the entire space medium to the instrument's measurement response is 1. Array resistivity instruments with different structures can be configured with geometric factors of different radial detection depths. The radial range of the formation model is divided into an intrusion zone and a undisturbed formation. The resistivity data actually measured by the array resistivity instrument in shallow and deep detection modes are used as the estimated values ​​of the resistivity of the intrusion zone and the resistivity of the undisturbed formation. At the same time, given different intrusion radii, the theoretical resistivity data of different detection modes is calculated by the geometric factor corresponding to the intrusion radius and matched with the actual measurement data. The theoretically calculated resistivity data of different detection modes corresponding to the smallest difference between the two is used as the array resistivity data after geometric factor correction.

[0092] Therefore, this embodiment, based on the array resistivity data of different detection modes collected by the array resistivity measuring instrument, calculates the theoretical resistivity data of different radial detection depths using only the theoretical geometric factors corresponding to different radial detection depths of the array resistivity measuring instrument and the geometric factor adaptive correction processing algorithm, without changing the instrument's mechanical structure and circuit design. This corrected resistivity data conforms to the sorting relationship of resistivity curves of different radial detection depths under mud invasion conditions, effectively eliminating the resistivity disorder phenomenon caused by the influence of complex well conditions on array resistivity measurement. This provides more accurate resistivity information of different radial detection depths for well logging interpreters and provides strong data support for the accurate evaluation of underground reservoirs.

[0093] In summary, without altering the instrument's mechanical structure, and based on the structure and measurement principle of the array resistivity logging instrument, geometric factors corresponding to different detection modes are set. The measured array resistivity curves are then corrected based on these geometric factors. This solves the problem of curve disorder at different detection depths under complex measurement environments, providing more reliable resistivity parameters for reservoir permeability assessment and accurate fluid identification.

[0094] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0095] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A geometric factor adaptive array resistivity curve correction method, characterized in that, Includes the following steps: Resistivity data actually measured using shallow and deep probe modes of an array resistivity instrument are used as estimates of resistivity in the intrusive zone and resistivity in the undisturbed formation. Given the intrusion radius, the corresponding geometric factor is calculated and the theoretical resistivity data for different detection modes are obtained through an adaptive correction processing algorithm; The theoretical resistivity data is matched with the actual measured data to obtain the theoretically calculated resistivity data corresponding to the minimum difference between the two, which is used as the array resistivity data after geometric factor correction. The array resistivity data corrected by the geometric factor eliminates the resistivity disorder phenomenon in array resistivity measurement. The geometric factor is a quantitative representation parameter of the intrusion radius at different detection depths. The geometric factor is calculated by Nth-order polynomial fitting, with the intrusion radius as the independent variable and the geometric factor as the dependent variable. The calculation is completed by combining the polynomial fitting coefficients corresponding to each detection depth. The fitting coefficients are adjusted accordingly with different detection depths. It also includes the calculation steps for the invasion radius and the geometric factors of multiple detection depths: the invasion radius is taken within a preset minimum and maximum range, the minimum value is greater than the wellbore radius, and the maximum value is limited by the deepest detection depth of the array resistivity instrument. The invasion radius changes gradually from the minimum to the maximum value. For different target detection depths of the instrument, the corresponding polynomial fitting formula is used to calculate the geometric factors. Each detection depth is matched with a dedicated polynomial fitting coefficient. For the same invasion radius, the geometric factors corresponding to different detection depths can be calculated independently. The theoretical array resistivity data for different radial detection depths are obtained by using the estimated resistivity of the intrusion zone, the estimated resistivity of the original formation, and the geometric factor of the intrusion radius corresponding to each detection depth as core calculation parameters, combined with the response principle of array resistivity logging, through weighted calculation. For each preset intrusion radius, a set of theoretical array resistivity data for the entire detection depth can be calculated.

2. The geometric factor adaptive array resistivity curve correction method according to claim 1, characterized in that: The estimated values ​​of resistivity in the intrusive zone and resistivity in the original formation are based on multiple sets of array resistivity curve data measured by the array resistivity instrument. The values ​​are obtained by weighting the curve data at different detection depths by setting corresponding weighting factors. The weighting factors can be adaptively adjusted according to the actual logging conditions.

3. The geometric factor adaptive array resistivity curve correction method according to claim 1, characterized in that: By calculating the Euclidean distance between theoretical array resistivity data and actual measured array resistivity data, the minimum difference between the two is quantitatively selected. A set of theoretical array resistivity data for the entire detection depth is integrated into one row vector, and the corresponding measured array resistivity data is integrated into another row vector. The Euclidean distance is then calculated based on the two row vectors.

4. The geometric factor adaptive array resistivity curve correction method according to claim 3, characterized in that: The Euclidean distance is the square root of the sum of the squares of the differences between the corresponding elements of two row vectors. For each intrusion radius within the range of values, the corresponding Euclidean distance is calculated once. The Euclidean distances corresponding to all intrusion radii are calculated and compared iteratively, and the intrusion radius corresponding to the minimum Euclidean distance is selected. The theoretical array resistivity data under this radius is the array resistivity data after geometric factor correction.

5. The geometric factor adaptive array resistivity curve correction method according to claim 4, characterized in that: The corrected array resistivity data follows a forward or reverse order pattern, meaning that the greater the detection depth, the higher the resistivity value in a low-impact, high-resistivity layer, and the lower the resistivity value in a high-impact, low-resistivity layer.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the geometric factor adaptive array resistivity curve correction method as described in any one of claims 1-5.

7. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the geometric factor adaptive array resistivity curve correction method as described in any one of claims 1-5.

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