A method for identifying a formation fluid, a computer device and a readable storage medium

Abstract

The application provides a method for identifying formation fluid, a computer device and a readable storage medium. The method comprises: performing equidistant processing and data extraction on mud logging data of a target layer section of a tested oil well in a target area to obtain a plurality of groups of time period data; processing each group of time period data to obtain a temperature increment rate with time, the processing comprising: time standardization processing, adding an accumulated time item; setting a unified accumulated time-temperature starting point; performing accumulated time and temperature correlation analysis; integrating a plurality of increment rates, combining with oil testing data, and establishing a discrimination standard. The computer device comprises at least one processor and a memory storing program instructions, the program instructions being used for executing the instructions of the above method. The computer readable storage medium stores computer program instructions. The application can directly apply time domain mud logging data, so that mud logging information is completely presented, and is beneficial to the implementation of fluid key information and the judgment of data reliability.

Description

Technical Field

[0001] This invention relates to the field of geological evaluation while drilling, and more specifically, to a method for identifying formation fluids, a computer device, and a readable storage medium. Background Technology

[0002] Currently, formation fluid property identification while drilling mainly relies on the "same-direction" changes of various logging parameters that are responsive to formation fluid properties, such as temperature, conductivity, chloride ions, and logging resistivity, or uses fluid discrimination techniques based on these parameters.

[0003] However, under the conditions of currently widely used oil-based drilling fluids, the electrical conductivity of logging is completely lost, chloride ion concentration is generally distorted, and gas logging parameters are also affected to some extent, with only temperature being less affected. Existing technologies utilize multiple logging parameters in combination, making them unusable under oil-based drilling fluid conditions. Summary of the Invention

[0004] The purpose of this invention is to overcome at least one of the aforementioned shortcomings of the prior art. For example, one objective of this invention is to achieve accurate determination of the properties of formation fluids.

[0005] To achieve the above objectives, the present invention provides a method for identifying formation fluids.

[0006] The method may include the following steps: performing equal-interval processing and data extraction on the logging data of the target layer of the tested well in the target area to obtain several sets of time period data; wherein, equal-interval processing includes processing for consistent time intervals, and data extraction includes data corresponding to the temperature rise to the peak stage during the circulation process after the tested well has settled in that layer; performing comprehensive processing on each set of time period data to obtain the temperature increase rate over time corresponding to each time period; wherein, comprehensive processing includes: time standardization processing, adding a cumulative time term; setting a unified cumulative time-temperature starting point; performing correlation analysis between cumulative time and temperature; and, when there are multiple sets of time period data and each corresponds to at least two fluids, integrating the increase rates corresponding to multiple sets of time periods, and combining them with the oil testing data to establish a discrimination criterion.

[0007] Alternatively, the logging data may include multiple data pairs, each data pair including corresponding time intervals, well depths, flow rates, and temperatures.

[0008] Alternatively, the cyclic process may include a process in which the displacement is stable and non-zero.

[0009] Alternatively, the displacement is considered stable when it is between 14 and 23 L / s.

[0010] Optionally, the time standardization process includes: selecting the average value or a commonly used value of the displacement as the standard displacement based on the changes in displacement of each well in the target area during drilling in the target formation, and standardizing the time interval.

[0011] Alternatively, the time standardization process can be performed using Equation 1, which is: t 标准 =t 间隔 ×V / V 标准 , where t 标准 For standard time, t 间隔 V represents the time interval, and V represents the displacement. 标准 This is the standard displacement.

[0012] Optionally, adding a cumulative time item includes adding a cumulative time item to the time period data. The cumulative time is obtained using Equation 2, which is: Among them, t 累计 The cumulative time is n, where n is the number of data pairs in the time period.

[0013] Optionally, setting a unified cumulative time-temperature starting point includes: determining a suitable starting temperature value based on temperature changes within the target area; and adjusting the cumulative time for the temperature to reach the starting temperature value in the time period data to a unified value.

[0014] Alternatively, the appropriate initial temperature value may include the maximum of the lowest temperatures during the drilling process of each well in that formation.

[0015] Alternatively, the rate of temperature increase over time can be calculated using Equation 3, which is:

[0016] W = a·ln(t) 累计 )+b, where W is temperature, a is the rate of temperature increase, b is a coefficient, and t 累计 This represents the cumulative time.

[0017] In another aspect, the present invention provides a computer device.

[0018] The computer device includes: at least one processor, and a memory storing program instructions, wherein the program instructions are configured to be executed by the at least one processor, the program instructions including instructions for performing the formation fluid discrimination method as described above.

[0019] In another aspect, the present invention provides a computer-readable storage medium.

[0020] The computer-readable storage medium stores computer program instructions thereon, characterized in that the computer program instructions, when executed by a processor, implement the formation fluid discrimination method as described above.

[0021] Compared with the prior art, the beneficial effects of the present invention include at least one of the following:

[0022] (1) The method of the present invention is simple and can accurately determine the properties of formation fluids during drilling.

[0023] (2) The method of the present invention can be applied not only under water-based drilling fluid conditions, but also under oil-based drilling fluid conditions.

[0024] (3) The present invention can directly apply time-domain logging data, so that logging information is fully presented, which is conducive to the implementation of key fluid information and the judgment of data reliability.

[0025] (4) This invention makes precise use of the logging temperature parameter, which is the only one that can be used to determine the properties of formation fluids under oil-based drilling fluid conditions and is not significantly affected. Existing technologies have not applied the logging temperature parameter to the time domain and have not achieved single-parameter determination.

[0026] (5) This invention creates a new parameter, the rate of temperature increase over time, and deeply mines the fluid information reflected in the temperature data changes, thus elevating the application of temperature data to a new level. Attached Figure Description

[0027] The above and other objects and / or features of the present invention will become clearer from the following description taken in conjunction with the accompanying drawings, in which:

[0028] Figure 1 This diagram illustrates the data extraction during the time period when the temperature gradually rises to its peak in step b of the present invention.

[0029] Figure 2 The diagram illustrates the correlation analysis between cumulative time and temperature in step e and the establishment of the discrimination criteria in step f of the present invention.

[0030] Figure 3 A schematic diagram showing the division between the water and air zones is provided. Detailed Implementation

[0031] In the following, a method for identifying formation fluids, a computer device, and a readable storage medium of the present invention will be described in detail with reference to exemplary embodiments.

[0032] On one hand, this invention uses time-domain logging data as a foundation, taking the same time-temperature as a unified starting point. Through standardization of time by drilling fluid discharge rate, it calculates the rate of temperature increase over time during different pump restart cycles after pump shutdowns. Based on the differences in temperature increase rates in formations containing different fluids, a discrimination standard or chart is established, forming a discrimination method.

[0033] Exemplary Example 1

[0034] This exemplary embodiment provides a method for identifying formation fluids.

[0035] The discrimination method may include:

[0036] The logging data of the target layer in the test wells within the target area are processed with equal intervals and data is extracted to obtain several sets of time period data. Among them, the equal interval processing includes processing with consistent time intervals, and the data extraction includes the data corresponding to the temperature rise to the peak stage during the circulation process after the test wells have settled in this layer.

[0037] The data for each time period are comprehensively processed to obtain the rate of temperature increase over time for each time period. The comprehensive processing includes: time standardization, adding a cumulative time term; setting a unified starting point for cumulative time and temperature; and performing correlation analysis between cumulative time and temperature.

[0038] When there are multiple sets of time period data, each corresponding to at least two fluids, the increment rates corresponding to the multiple time periods are integrated, and the oil test data are combined to establish a discrimination criterion.

[0039] In this embodiment, the logging data includes multiple data pairs, each of which includes a corresponding time interval, well depth, discharge rate, and temperature.

[0040] In this embodiment, the cyclic process includes a process in which the displacement is stable and non-zero.

[0041] In this embodiment, the displacement is considered stable when it is between 14 and 23 L / s. Furthermore, the displacement is between 18 and 22 L / s, for example, 19, 20, or 21 L / s.

[0042] In this embodiment, the time standardization process may include: selecting the average value or a commonly used value of the displacement as the standard displacement based on the changes in displacement of each well in the target area during the drilling process in the target layer, and standardizing the time interval.

[0043] In this embodiment, the time standardization process is performed using Equation 1, which is: t 标准 =t 间隔 ×V / V 标准 .

[0044] Among them, t 标准 For standard time, t 间隔 V represents the time interval, and V represents the displacement. 标准 This is the standard displacement.

[0045] In this embodiment, adding a cumulative time item includes adding a cumulative time item to the time period data. The cumulative time is obtained using Equation 2, which is:

[0046] Among them, t 累计 The cumulative time is n, where n is the number of data pairs in the time period.

[0047] In this embodiment, setting a unified cumulative time-temperature starting point includes: determining a suitable starting temperature value based on temperature changes within the target area; and adjusting the cumulative time for the temperature to reach the starting temperature value in the time period data to a unified value.

[0048] In this embodiment, the appropriate initial temperature value may include: the maximum value among the lowest temperature values ​​during the drilling process of each well in this section, that is, the maximum value among multiple lowest temperature values.

[0049] In this embodiment, the rate of temperature increase over time can be calculated according to Equation 3, which is:

[0050] W = a·ln(t) 累计 )+b.

[0051] Where W is temperature, a is the temperature increase rate, b is a coefficient, and t 累计 This represents the cumulative time.

[0052] Exemplary Example 2

[0053] This exemplary embodiment provides a method for identifying formation fluids. The method may include the following steps:

[0054] a. Collect logging data and oil testing data for a specific time period from wells already tested in the study area, and process the time-domain logging data at equal intervals. The oil testing data will be used in subsequent step f.

[0055] Due to the different logging equipment, the sampling interval of logging data in the time domain generally varies. By processing the time interval equally, the time interval of the data is unified.

[0056] The logging data utilized in this invention includes: time interval, well depth, displacement, and temperature. Among these, the time interval is the basis for cumulative time calculation, the well depth is key to the correspondence between time interval data and oil testing conclusions, the displacement is an important parameter for time standardization, and temperature is the core of the method of this invention.

[0057] b. Extract the time period during which the temperature rises to its peak during the circulation process after each well has settled in that layer, and delete the data from the settled period.

[0058] Figure 1This diagram illustrates the data extraction during the time period when the temperature gradually rises to its peak in step b of the present invention. Curve 1 represents the displacement, and curve 2 represents the temperature. During drilling, the drilling fluid exists in two states: static and circulating. The most obvious criterion for distinguishing between these two states is the displacement; the displacement is zero when static and non-zero when circulating. Figure 1 During medium-speed circulation, the displacement is typically 16–20 L / s. Figure 1 As can be seen, in segment ①, the temperature rise is a single upward curve, gradually increasing without pause from rest to the cycle; in segment ②, the temperature rise is a multi-segment upward curve, with an overall upward trend, but several brief periods of stagnation (marked in area ③, where displacement is zero), followed by a brief temperature drop before continuing to rise. This invention aims to extract the data from the temperature rise segments during the cycle (the portion marked by the box above the temperature curve), therefore, the data from these brief periods of temperature drop have been removed. It should be noted that the time period data mentioned in this invention refers to the data from the period from rest to the cycle, during which the temperature gradually rises to its peak value.

[0059] In the time-domain logging data, temperature data exhibits a wave-like fluctuation. During the cyclic process (when the flow rate is stable and not zero), the temperature gradually increases over time, while during the static process (when the flow rate is zero), the temperature rapidly decreases over time. The flow rate varies depending on the region, formation, and depth. The stability of the flow rate can be determined based on specific conditions. For example, in data from a target formation in the Sichuan Basin, the flow rate ranges from 14 to 23 L / s, with a common range of 18 to 22 L / s. 20 L / s can be selected as the standard flow rate. In this invention, the flow rate is primarily used to determine the drilling fluid state and to standardize the time.

[0060] Extract the data from the logging data of each well in the time domain of this layer, showing the time period during which the temperature gradually rises to the peak after the cycle has stopped. There may be short periods of stillness in this process, so delete the data from the still periods.

[0061] Here, the following explanation is provided: A single well can yield multiple sets of time-period data. Taking a specific target formation as an example, drilling a well takes more than two months, during which many time-period data points can be extracted. However, the testing section is often only a part of the target formation, resulting in significantly fewer extractable time-period data points, such as 1 to 3 sets. Each set of time-period data needs to be processed according to steps a to e in this invention to obtain the cumulative time and temperature data for each segment and calculate the temperature increase rate. However, not every well depth corresponding to each set of time-period data has undergone testing. Only time-period data with testing results at the corresponding well depth has the corresponding fluid properties, can be used to establish a discrimination method, and requires integration in subsequent step f. For establishing a method, the larger the data base, the more reliable the method; and the more wells there are, the larger the data base.

[0062] It should be noted that the "equal spacing processing" in step a and the "extracting time period data" in step b do not have a specific order. For example, you can extract the time period data first and then perform equal spacing processing.

[0063] c. Establish a "cumulative time" channel in the extracted time period data, and standardize the time using displacement.

[0064] The logging data in the time domain uses the sampling time as the coordinate axis and establishes "cumulative time" as the new coordinate axis. The cumulative time is the sum of the time.

[0065]

[0066] In equation (1), t 累计 Let t be the cumulative time, n be the amount of data extracted for the time period, and t be the total time. 间距 This represents the time interval.

[0067] Based on the variation of displacement during drilling in this layer of each well in the study area, the average value or commonly used value is selected as the standard displacement, and the time is standardized.

[0068] t 标准 =t 间距 ×V / V 标准 (2)

[0069] In equation (2), t 标准 For standard time, V is displacement. 标准 This is the standard displacement.

[0070] Therefore, Equation 3 is adjusted to

[0071]

[0072] d. Set a uniform cumulative time-temperature starting point.

[0073] Based on the temperature variations within the study area, a suitable initial temperature value is selected, with the selection criterion being the upper limit of the lowest temperature value during drilling of each well in that layer. The cumulative time for the temperature to reach the initial temperature value in the extracted time period data is adjusted to a uniform value, which can be selected according to the actual data conditions.

[0074] The initial temperature value is the starting temperature, primarily determined by the upper limit of the lowest temperature drop observed in each well within the study area when it is stationary in that stratum. For example, well A has a minimum temperature drop of 20℃ and a peak of 50℃ after stabilization; well B has a minimum of 30℃ and a peak of 60℃; and well C has a minimum of 40℃ and a peak of 70℃. To ensure a uniform initial temperature value for each well, the initial temperature value must be set above the upper limit of the minimum values ​​for the three wells, which is 40℃. If it is too low, the initial temperature value cannot be extracted from well C; if it is too high, it is too close to the peak temperature of 50℃ in well A, leaving too little room for temperature increase and making data extraction very difficult. Therefore, the initial temperature value needs to be selected based on the actual data conditions. The data processing procedure is shown in Table 1. On April 11, 2022, at 03:44:52, the well began circulation at a rate of 13.4 L / s. As the circulation time increased, the temperature gradually rose. At 04:01:52, the temperature reached 40℃, so the cumulative time for this point was set to 50 minutes. The cumulative time continued to accumulate according to the standard time, which was processed using the displacement-standardized formula. At 04:07:52, the temperature reached 41.5℃. At this point, there was a brief period of stillness, and the temperature dropped. By 04:15:52, the temperature had returned to 41.7℃. The 8 minutes of temperature drop during this period were due to stillness and were removed (i.e., the deletion of the stillness segment data in step b). Finally, the cumulative time and temperature data from the initial temperature to the peak temperature were obtained, which is the core data of this invention.

[0075] Each set of time period data extracted in this invention exists independently, but it still needs to be processed uniformly. For example, each set of time period data starts with the cumulative time of 50 minus the temperature of 40.

[0076] Table 1 shows the time standardization process in step c and the cumulative time-temperature start point setting in step d.

[0077]

[0078]

[0079] e. Perform a correlation analysis between the cumulative time and temperature to determine the rate of temperature increase over time.

[0080] Correlation analysis is performed between cumulative time and temperature to determine the correlation relationship. This is typically an exponential relationship.

[0081] W = a·ln(t) 累计 )+b (4)

[0082] In equation (4), W is temperature, a is the temperature increase rate, and b is a coefficient.

[0083] By performing correlation analysis between the cumulative time and temperature in each data segment, we can fit the logarithmic correlation trend between the two and calculate the rate of temperature increase over time. For example... Figure 2 In the first air layer, the fitted temperature increase rate over time is 6.781, which is an important attribute of each data segment. Figure 2 In the equation, 1, 2, and 3 represent the fitted logarithmic trends corresponding to ① gas layer, ② gas layer, and ③ water layer, respectively, and 4 represents the discrimination standard line set in the subsequent step f. Figure 2 The equations corresponding to 1, 2, 3 and 4 in the equations are y = 6.781ln(x) + 12.838, y = 5.6239ln(x) + 17.432, y = 9.0185ln(x) + 4.3622 and y = 7.3504ln(x) + 11.245, respectively.

[0084] f. Integrate the extracted time period data to calculate the temperature increase rate, combine it with the oil test data of each well, and establish a discrimination standard or chart based on the differences in temperature increase rate of different formation fluid properties to form a discrimination method.

[0085] Integration involves projecting multiple time-period data points with fluid properties, processed through steps a to e, onto the same correlation map. The more data integrated, the better it is for presenting data point trends, for determining the boundaries between air and water layer data points, and for establishing discrimination criteria, including determining the distribution boundaries of data points (discrimination chart) and the boundaries of temperature increase rate (discrimination method).

[0086] Establishing discrimination criteria or charts may include: projecting multiple time-period data points with fluid properties, processed through steps a to e, onto the same correlation map; and, following the principle of separating gas layer data points and water layer data points as much as possible, defining discrimination criteria lines and gas and water zones. Based on these boundaries, a formation fluid property discrimination chart is formed. Simultaneously, based on these boundaries, a discrimination criterion for temperature increase rate can be determined, serving as the basis for distinguishing between water and gas layers, thus forming a formation fluid property discrimination method. Of course, besides gas and water layers, the method of this invention can also be used for the division of oil layers from other layers.

[0087] Figure 2 The data comes from a tested oil well in the Sichuan Basin. The well was tested in two sections: one for gas and one for water. Figure 1 The data for the period from March 26th to March 27th, 2021, represents the time period data for the well section where the well was tested and found to be a gas-bearing zone. It includes data for zone ① and zone ②, which are two sets of time period data within the well section where the well was tested and found to be a gas-bearing zone. Additionally, data for zone ③ was extracted from the time period data of the well section where the well was tested and found to be a water-bearing zone.

[0088] Based on the oil test results, corresponding attributes were assigned to layers ① (gas layer), ② (gas layer), and ③ (water layer), and the three data segments were projected onto the same correlation map. Figure 2 As can be seen above, there is a clear boundary between the data points of the gas layer and the water layer, and the discrimination criterion is the boundary that can effectively separate the data points of the gas layer and the water layer. Following the principle of separating the gas layer data points and the water layer data points as much as possible, a discrimination criterion line 4 was set, which is... Figure 2 and Figure 3 As can be seen, this line completely separates the two, achieving a 100% differentiation rate. Furthermore, considering the temperature increase rate, the standard line's temperature increase rate is 7.3504, which also distinguishes between gas and water layers. Based on these two standards, a basis can be provided for future well drilling to determine the properties of formation fluids.

[0089] This invention can project time-period data from multiple wells with fluid properties in the same section within the same region, processed through steps a to e, onto the same correlation map to divide different types of layers (e.g., gas layers and water layers).

[0090] Therefore, the innovative aspects of this method include:

[0091] (1) Apply time-domain logging data as the data basis for fluid discrimination.

[0092] Previous methods for determining formation fluid properties primarily relied on logging data converted from the time domain to the depth domain. However, this conversion process obscured a significant amount of logging information, including crucial details. This invention directly utilizes time-domain logging data, presenting the complete logging information and facilitating the identification of key fluid information and the assessment of data reliability. More importantly, it opens up a new field of time-domain data for logging research.

[0093] (2) A new logging fluid discrimination parameter, temperature increment rate, and its calculation method are proposed.

[0094] Previously, in the process of determining the properties of formation fluids, the use of temperature mainly relied on the changes in the curve over depth or the intersection characteristics with curves for conductivity, chloride ions, etc. In this invention, a new parameter, the rate of temperature increase over time, is created to deeply mine the fluid information reflected in the changes in temperature data, thus elevating the application of temperature data to a new level.

[0095] On the other hand, the formation fluid identification method of the present invention can be programmed into a computer program and the corresponding program code or instructions can be stored in a computer-readable storage medium. When the program code or instructions are executed by a processor, the processor performs the above method. The processor and memory described below can be included in a computer device.

[0096] Exemplary Example 3

[0097] This exemplary embodiment provides a computer device, including:

[0098] At least one processor;

[0099] A memory storing program instructions configured to be executed by the at least one processor, the program instructions including a method for determining formation fluids according to exemplary embodiment 1 or 2.

[0100] Exemplary Example 4

[0101] This exemplary embodiment provides a computer-readable storage medium.

[0102] The storage medium stores a computer program. When the computer program instructions are executed by a processor, they implement the formation fluid discrimination method as described in Exemplary Embodiment 1 or 2.

[0103] The computer-readable storage medium can be any data storage device that stores data that can be read by a computer system. Examples of computer-readable storage media include: read-only memory, random access memory, read-only optical disc, magnetic tape, floppy disk, optical data storage device, and carrier waves (such as data transmission via the Internet through wired or wireless transmission paths).

[0104] Although the present invention has been described above in conjunction with exemplary embodiments and accompanying drawings, those skilled in the art should understand that various modifications can be made to the above embodiments without departing from the spirit and scope of the claims.

Claims

1. A method for identifying formation fluids, characterized in that, The method includes the following steps: The logging data of the target layer in the test wells within the target area are processed with equal intervals and data is extracted to obtain several sets of time period data. Among them, the equal interval processing includes processing with consistent time intervals, and the data extraction includes the data corresponding to the temperature rise to the peak stage during the circulation process after the test wells have settled in this layer. The data for each time period are comprehensively processed to obtain the rate of temperature increase over time for each time period. The comprehensive processing includes: time standardization, adding a cumulative time term; setting a unified starting point for cumulative time and temperature; and performing correlation analysis between cumulative time and temperature. When there are multiple sets of time period data and each corresponds to at least two fluids, integrate the increase rates corresponding to the multiple time periods, combine them with oil test data, and establish judgment criteria or charts. The establishment of the discrimination criteria or chart includes: projecting multiple time period data with fluid properties onto the same correlation map to divide the discrimination criteria line and gas and water regions; forming a formation fluid property discrimination chart based on the discrimination criteria line; or determining the discrimination criteria of temperature increase rate based on the discrimination criteria line, which serves as the basis for distinguishing water and gas layers. The cyclic process includes a process in which the displacement is stable and non-zero; The time standardization process includes: based on the changes in displacement of each well in the target area during the drilling process of the target layer, selecting the average value or a commonly used value of displacement as the standard displacement, and standardizing the time interval. The time standardization process is performed using Equation 1, which is: t 标准 = t 间隔 × V / V 标准 ,in, t 标准 Standard time, t 间隔 For time intervals, V For displacement, V 标准 Standard displacement; The addition of a cumulative time item includes adding a cumulative time item to the time period data. The cumulative time is obtained using Equation 2, which is: ,in, t 累计 For cumulative time, n This represents the number of data pairs in the time period data. Setting a unified cumulative time-temperature starting point includes: determining a suitable starting temperature value based on temperature changes within the target area; and adjusting the cumulative time for the temperature to reach the starting temperature value in the time period data to a unified value. The rate of temperature increase over time can be calculated using Equation 3, which is: W = a · ln ( t 累计 )+b, where, W For temperature, a For the rate of temperature increase, b For coefficients, t 累计 This represents the cumulative time.

2. The method for identifying formation fluids according to claim 1, characterized in that, The logging data includes multiple data pairs, each pair containing corresponding time intervals, well depths, discharge rates, and temperatures.

3. The method for identifying formation fluids according to claim 1, characterized in that, The displacement is considered stable when the displacement is between 14 and 23 L / s.

4. The method for identifying formation fluids according to claim 1, characterized in that, The appropriate initial temperature value includes the maximum value among the lowest temperature values ​​during the drilling process of each well in that section.

5. A computer device, characterized in that, include: At least one processor; A memory storing program instructions configured to be executed by the at least one processor, the program instructions including instructions for performing the method according to any one of claims 1 to 4.

6. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method of any one of claims 1 to 4.

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