Water injection well DTS temperature return steady state curve prediction method, system, equipment and medium

Abstract

The invention discloses a water injection well DTS temperature return steady-state curve prediction method, system and equipment and a medium, and belongs to the technical field of petroleum geophysical exploration and development. Based on the close correlation between the heat conduction speed and the temperature difference between substances, when a water injection well is shut down, the temperature difference between the formation temperature and the shaft temperature is maximum, and the heat conduction speed between the formation temperature and the shaft temperature is fastest; as the temperature difference between the formation temperature and the shaft temperature is gradually reduced, the heat conduction speed is gradually reduced, the whole relation is approximate to a logarithmic curve, and the steady-state temperature prediction of the water injection well is realized by utilizing the theory; according to the method, the shortest collection time and the temperature return time are determined through historical actually measured temperature return data, then the needed simulation time is obtained, the temperature return simulation curve model is built, and finally the time point corresponding to the needed simulation time is input into the temperature return simulation curve model to form the DTS temperature return steady state curve so as to complete simulation. According to the method, the sampling distributed fitting thought is adopted, the well shut-in steady-state temperature of the water injection well is simulated, and the effective rate of optical fiber DTS logging information is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of petroleum geophysical exploration and development, and in particular relates to a method, system, equipment and medium for predicting a DTS temperature recovery steady-state curve of a water injection well. Background Art

[0002] With the deepening of exploration and development, various oil fields have generally adopted horizontal well staged fracturing technology to increase the production of single wells, but there has been a lack of effective means to dynamically monitor and evaluate the production capacity of horizontal wells. In recent years, distributed fiber optic logging (DTS / DAS) technology has the advantages of small size, light weight, anti-vibration, anti-interference, low power consumption, high sensitivity, ultra-high temperature and pressure resistance, etc., and has received widespread attention from users. Its application surface, application scenarios and application scale are constantly expanding, such as shale oil and gas horizontal well dynamic output monitoring, fracturing monitoring, water plugging guidance, etc. The rapid development of distributed fiber optic logging dynamic monitoring technology makes horizontal well staged fracturing monitoring and evaluation possible, and is expected to become a technical tool to guide production logging to the middle and high end.

[0003] However, there are still many problems to be solved in the collection and interpretation of fiber optic logging data. For example, when conducting fiber optic monitoring of water injection wells in oil fields, it is necessary to rely on long-term well shutdown to obtain steady-state formation temperature. Long-term well shutdown will have a great impact on oil well production, and it is difficult to obtain formation temperature by fiber optic monitoring under short-term well shutdown conditions. The existing technology mainly uses non-steady-state shut-in temperature to calculate stratified flow. Although it can predict the shut-in temperature, this method leads to a large error between the predicted result and the actual result, which is difficult to meet production requirements. Summary of the invention

[0004] In order to overcome the shortcomings of the above-mentioned technology, the present invention provides a method, system, equipment and medium for predicting the DTS temperature recovery steady-state curve of an injection well, which can solve the technical problem that the prior art uses non-steady-state shut-in temperature to calculate the stratified flow rate to predict the temperature recovery temperature, resulting in large deviations in the results.

[0005] In order to achieve the above object, the present invention adopts the following technical solution:

[0006] A method for predicting a DTS temperature recovery steady-state curve of a water injection well, comprising:

[0007] S1: Obtain historical measured temperature recovery data, and determine the shortest acquisition time and the temperature recovery time when the temperature reaches a steady state according to the historical measured temperature recovery data;

[0008] S2: The required simulation time is obtained based on the shortest acquisition time and the temperature recovery time, and a temperature recovery simulation curve model is built in combination with the historical measured temperature recovery data;

[0009] S3: Input the time point corresponding to the required simulation time into the temperature recovery simulation curve model to simulate and form a DTS temperature recovery steady-state curve.

[0010] Furthermore, in S1, the measured temperature recovery curve is obtained by using the historical measured temperature recovery data, and the temperature recovery time when the temperature recovery temperature reaches a steady state is determined by using the measured temperature recovery curve.

[0011] Furthermore, in S1, the fluctuation value of the warming temperature is less than 0.1°C / h.

[0012] Furthermore, in S2, the calculation formula for the required simulation time is:

[0013] Required simulation time = temperature recovery time - shortest acquisition time.

[0014] Furthermore, in S2, the formula corresponding to the temperature recovery simulation curve model is:

[0015] y = a log b x

[0016] Among them, y is the recovery temperature, a and b are fitting constants, and x is time.

[0017] Furthermore, historical measured temperature recovery data is obtained through sampling, and the simulation of the DTS temperature recovery steady-state curve is completed according to the sampling time interval.

[0018] Furthermore, in S3, three parameters, namely temperature prediction, cut-off time and noise superposition, are added to simulate the DTS temperature recovery steady-state curve.

[0019] A water injection well DTS temperature recovery steady-state curve prediction system, used to implement the steps of the water injection well DTS temperature recovery steady-state curve prediction method, comprising:

[0020] A data acquisition module is used to acquire historical measured temperature recovery data, and determine the shortest acquisition time and the temperature recovery time when the temperature reaches a steady state according to the historical measured temperature recovery data;

[0021] The model building module is used to obtain the required simulation time based on the shortest acquisition time and the temperature recovery time, and to build a temperature recovery simulation curve model in combination with the historical measured temperature recovery data;

[0022] The curve simulation module is used to input the time point corresponding to the required simulation time into the temperature recovery simulation curve model to simulate and form a DTS temperature recovery steady-state curve.

[0023] A device comprising:

[0024] Memory for storing computer programs;

[0025] The processor is used to implement the steps of the above-mentioned method for predicting the DTS temperature recovery steady-state curve of the water injection well when executing the computer program.

[0026] A computer-readable storage medium stores a computer program, which is used to implement the steps of the above-mentioned method for predicting the DTS temperature recovery steady-state curve of the water injection well when executed by a processor.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] The present invention provides a method for predicting a DTS temperature recovery steady-state curve of an injection well. The present invention is based on the principle of heat conduction, that is, the heat conduction speed is closely related to the temperature difference between substances. When the injection well is shut in, the temperature difference between the formation temperature and the wellbore temperature is the largest, and the heat conduction speed between the two is the fastest. As the temperature difference between the formation temperature and the wellbore temperature gradually decreases, the heat conduction speed gradually slows down, and the entire relationship is approximately a logarithmic curve. The theory is used to predict the steady-state temperature of the injection well. The present invention determines the shortest acquisition time and the temperature recovery time through historical measured temperature recovery data, and then obtains the required simulation time and builds a temperature recovery simulation curve model. Finally, the time point corresponding to the required simulation time is input into the temperature recovery simulation curve model to form a DTS temperature recovery steady-state curve to complete the simulation. The present invention adopts a sampling distributed fitting idea to simulate the shut-in steady-state temperature of the injection well, thereby improving the efficiency of optical fiber DTS logging data. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 A flow chart of a method for predicting a DTS temperature recovery steady-state curve of a water injection well provided in an embodiment of the present invention;

[0030] Figure 2 A comparison diagram of the processing results of the steady-state curve and the non-steady-state curve provided in an embodiment of the present invention;

[0031] Figure 3 A schematic diagram of the time required for the temperature to reach a steady state provided by an embodiment of the present invention;

[0032] Figure 4 A schematic diagram of distributed temperature recovery simulation prediction provided by an embodiment of the present invention;

[0033] Figure 5 An interface diagram of a distributed temperature rise simulation prediction program provided by an embodiment of the present invention;

[0034] Figure 6 The measured DTS curve of Yu 9-X well provided in the embodiment of the present invention;

[0035] Figure 7 The simulated DTS curve of the Yu9-X well provided in the embodiment of the present invention;

[0036] Figure 8A flow chart of a method for predicting a DTS temperature recovery steady-state curve of a water injection well provided by the present invention;

[0037] Fig. 9 A schematic diagram of the structure of a water injection well DTS temperature recovery steady-state curve prediction system provided by the present invention. DETAILED DESCRIPTION

[0038] The present invention provides a method for predicting a DTS temperature recovery steady-state curve of a water injection well. Figure 8 As shown, the following steps are included:

[0039] S1: Obtain historical measured temperature recovery data, and determine the shortest acquisition time and the temperature recovery time when the temperature reaches a steady state according to the historical measured temperature recovery data;

[0040] S2: The required simulation time is obtained based on the shortest acquisition time and the temperature recovery time, and a temperature recovery simulation curve model is built in combination with the historical measured temperature recovery data;

[0041] S3: Input the time point corresponding to the required simulation time into the temperature recovery simulation curve model to simulate and form a DTS temperature recovery steady-state curve.

[0042] In S1, the measured temperature recovery curve is obtained by using the historical measured temperature recovery data, and the temperature recovery time when the temperature reaches a steady state is determined by using the measured temperature recovery curve.

[0043] The fluctuation value of the temperature recovery in S1 is less than 0.1°C / h.

[0044] In S2, the calculation formula for the required simulation time is:

[0045] Required simulation time = temperature recovery time - shortest acquisition time.

[0046] Correspondingly, the formula for the rewarming simulation curve model is:

[0047] y = a log b x

[0048] Among them, y is the recovery temperature, a and b are fitting constants, and x is time.

[0049] The historical measured temperature recovery data is obtained through sampling, and the simulation of the DTS temperature recovery steady-state curve is completed according to the sampling time interval.

[0050] In S3, three parameters, namely temperature prediction, cut-off time and noise superposition, are added to simulate the DTS warming steady-state curve. The setting of these three parameters can further improve the accuracy of curve simulation.

[0051] like Fig. 9As shown, the present invention also provides a water injection well DTS temperature recovery steady-state curve prediction system, including: a data acquisition module, a model building module and a curve simulation module; the data acquisition module is used to obtain historical measured temperature recovery data, and determine the shortest acquisition time and the temperature recovery time when the temperature reaches a steady state according to the historical measured temperature recovery data; the model building module is used to obtain the required simulation time according to the shortest acquisition time and the temperature recovery time, and build a temperature recovery simulation curve model in combination with the historical measured temperature recovery data; the curve simulation module is used to input the time point corresponding to the required simulation time into the temperature recovery simulation curve model to simulate and form a DTS temperature recovery steady-state curve.

[0052] The present invention also provides a device, comprising: a memory for storing a computer program; and a processor for implementing the steps of the method for predicting a DTS temperature recovery steady-state curve of an injection well when executing the computer program.

[0053] When the processor executes the computer program, the steps of predicting the DTS temperature recovery steady-state curve of the injection well are implemented, for example: obtaining historical measured temperature recovery data, determining the shortest acquisition time and the temperature recovery time when the temperature reaches a steady state according to the historical measured temperature recovery data; obtaining the required simulation time according to the shortest acquisition time and the temperature recovery time, and building a temperature recovery simulation curve model in combination with the historical measured temperature recovery data; inputting the time point corresponding to the required simulation time into the temperature recovery simulation curve model to simulate and form a DTS temperature recovery steady-state curve.

[0054] Alternatively, the processor implements the functions of each module in the above system when executing the computer program, for example: a data acquisition module, used to acquire historical measured temperature recovery data, and determine the shortest acquisition time and the temperature recovery time when the temperature reaches a steady state according to the historical measured temperature recovery data; a model building module, used to obtain the required simulation time according to the shortest acquisition time and the temperature recovery time, and build a temperature recovery simulation curve model in combination with the historical measured temperature recovery data; a curve simulation module, used to input the time point corresponding to the required simulation time into the temperature recovery simulation curve model, and simulate the formation of a DTS temperature recovery steady-state curve.

[0055] Exemplarily, the computer program can be divided into one or more modules / units, and the one or more modules / units are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units can be a series of computer program instruction segments that can complete preset functions, and the instruction segments are used to describe the execution process of the computer program in the water injection well DTS temperature recovery steady-state curve prediction device. For example, the computer program can be divided into a data acquisition module, a model building module and a curve simulation module; the specific functions of each module are as follows: a data acquisition module, which is used to obtain historical measured temperature recovery data, and determine the shortest acquisition time and the temperature recovery time when the temperature reaches a steady state according to the historical measured temperature recovery data; a model building module, which is used to obtain the required simulation time according to the shortest acquisition time and the temperature recovery time, and build a temperature recovery simulation curve model in combination with the historical measured temperature recovery data; a curve simulation module, which is used to input the time point corresponding to the required simulation time into the temperature recovery simulation curve model to simulate and form a DTS temperature recovery steady-state curve.

[0056] The DTS temperature recovery steady-state curve prediction device for water injection wells can be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The DTS temperature recovery steady-state curve prediction device for water injection wells can include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above is an example of a DTS temperature recovery steady-state curve prediction device for water injection wells, and does not constitute a limitation on the DTS temperature recovery steady-state curve prediction device for water injection wells. It can include more components than the above, or a combination of certain components, or different components. For example, the DTS temperature recovery steady-state curve prediction device for water injection wells can also include input and output devices, network access devices, buses, etc.

[0057] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. The processor is the control center of the injection well DTS temperature recovery steady-state curve prediction, and uses various interfaces and lines to connect various parts of the entire injection well DTS temperature recovery steady-state curve prediction device.

[0058] The memory can be used to store the computer program and / or module, and the processor implements various functions of the water injection well DTS temperature recovery steady-state curve prediction device by running or executing the computer program and / or module stored in the memory and calling the data stored in the memory.

[0059] The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, a flash card (FlashCard), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0060] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for predicting a DTS temperature recovery steady-state curve of an injection well are implemented.

[0061] If the module / unit integrated in the water injection well DTS temperature recovery steady-state curve prediction system is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0062] Based on such understanding, the present invention implements all or part of the processes in the above-mentioned method for predicting the DTS temperature recovery steady-state curve of water injection wells, and can also be completed by instructing related hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the above-mentioned method for predicting the DTS temperature recovery steady-state curve of water injection wells can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or preset intermediate form, etc.

[0063] The computer-readable storage medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0064] It should be noted that the content contained in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable storage media do not include electrical carrier signals and telecommunication signals.

[0065] Example

[0066] The present invention will be further described below in conjunction with the embodiments and drawings:

[0067] In order to solve the technical problem mentioned in the background technology that the prediction of the temperature recovery by calculating the stratified flow rate using non-steady-state shut-in temperature leads to a large error between the predicted result and the actual result, this embodiment provides a method for predicting the steady-state DTS recovery curve of an injection well. The theoretical basis of this method is: the heat conduction rate is closely related to the temperature difference between substances. When the injection well is shut in, the temperature difference between the formation temperature and the wellbore temperature is the largest, and the heat conduction rate between the two is the fastest; as the temperature difference between the formation temperature and the wellbore temperature gradually decreases, the heat conduction rate gradually slows down, and the entire relationship approximates a logarithmic curve; this theory is used to realize the steady-state temperature prediction of the injection well. Figure 1 As shown, the following steps are included:

[0068] Step 101: Determine the shortest acquisition time for the water injection well to recover temperature and the recovery time when the recovery temperature reaches a steady state.

[0069] Step 102: Determine the simulation time required for the temperature to reach a steady state.

[0070] Step 103: using the measured temperature recovery data, establish a temperature recovery curve function relationship at each depth point (ie, establish a temperature recovery simulation curve model).

[0071] Step 104: According to the simulation time determined in step 2, steady-state DTS data simulation is performed according to the acquisition interval to form a DTS temperature recovery steady-state curve.

[0072] The present invention is further explained below in conjunction with the actual measurement process of a specific water injection well:

[0073] The target well is the vertical well Yu9-X in XX Oilfield, with the highest bottom temperature of 57℃. Figure 2 As shown, Figure 2 This is a comparison of the flow rate results calculated by inverting the non-steady-state curve and the steady-state curve of Well Yu 9-X. It can be seen that the results obtained by the non-steady-state curve method have a great influence on the fiber optic interpretation results.

[0074] The present invention is described in detail below with reference to the accompanying drawings and specific implementation examples, as follows:

[0075] Step 101: Figure 3As shown in the figure, it is determined that the DTS well shut-in needs at least 10 hours of monitoring (determination of the shortest acquisition time). According to this requirement, on-site optical fiber data acquisition is carried out. The optical fiber instrument is put into the well in an open well state. After reaching the bottom, the open well working system is first monitored for 2 hours, and then the well is shut-in for 10 hours.

[0076] Step 102: Combined with the measured temperature recovery curve, determine the temperature recovery time corresponding to the temperature fluctuation <0.1°C / h. It takes 30 hours for the block temperature corresponding to the Yu9-X well to return to a steady state (determination of the temperature recovery time when the temperature reaches a steady state), so a 20-hour DTS curve simulation is required (determination of the required simulation time);

[0077] Step 103: Establish a specific logarithmic function curve using the relationship between the temperature change over time at each depth point of the injection well after the well is shut down, such as Figure 4 As shown in the figure, the functional relationship of each prediction point is established, and the number of temperature prediction channels, prediction deadline, and noise superposition value (such as Figure 5 As shown in the software interface), the accuracy of the simulation curve can be further improved.

[0078] Step 104: Taking the time point corresponding to the required simulation time as the input, maintaining the original sampling time interval, simulating the water injection well temperature recovery curve, and determining the last curve as the DTS temperature recovery steady-state curve; Figure 6 , Figure 7 The following are the measured temperature recovery curve and simulated temperature recovery curve (i.e., DTS temperature recovery steady-state curve) of Yu9-X well, respectively. Figure 6 and Figure 7 It can be seen from the two black boxes that the simulation results are very close to the measured results, the change trends are basically the same, and the simulation results are very accurate.

[0079] The specific procedures are as follows:

[0080]

[0081]

[0082] The present invention provides a method for predicting the DTS temperature recovery steady-state curve of an injection well, which adopts a sampling distributed fitting approach, determines the fiber temperature recovery cutoff time by region and scene, simulates the shut-in steady-state temperature of the injection well, and improves the efficiency of the fiber DTS logging data. The specific advantages are as follows:

[0083] This method uses measured data from different blocks to establish a regional prediction model to determine the shut-in monitoring time and production steady-state time; establish a distributed prediction model at each depth sampling point; and use different models to predict temperature recovery at different sampling points. This method has been applied in wells such as Chu 28-9 and Yu 9-15. The simulated temperature recovery is basically consistent with the measured temperature recovery. The temperature recovery simulation method is feasible and has good promotion and application value.

[0084] The above embodiment is only one of the implementation methods that can realize the technical solution of the present invention. The scope of protection claimed by the present invention is not limited only to this embodiment, but also includes changes, replacements and other implementation methods that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed by the present invention.

Claims

1. A method for predicting a DTS temperature recovery steady-state curve of a water injection well, characterized in that: include: S1: Obtain historical measured temperature recovery data, and determine the shortest acquisition time and the temperature recovery time when the temperature reaches a steady state according to the historical measured temperature recovery data; S2: The required simulation time is obtained based on the shortest acquisition time and the temperature recovery time, and a temperature recovery simulation curve model is built in combination with the historical measured temperature recovery data; S3: Input the time point corresponding to the required simulation time into the temperature recovery simulation curve model to simulate and form a DTS temperature recovery steady-state curve.

2. A method for predicting a DTS temperature recovery steady-state curve of a water injection well according to claim 1, characterized in that: In S1, the measured temperature recovery curve is obtained by using the historical measured temperature recovery data, and the temperature recovery time when the temperature reaches a steady state is determined by using the measured temperature recovery curve.

3. A method for predicting a DTS temperature recovery steady-state curve of a water injection well according to claim 1, characterized in that: In S1, the fluctuation value of the temperature recovery is less than 0.1°C / h.

4. A method for predicting a DTS temperature recovery steady-state curve of a water injection well according to claim 1, characterized in that: In S2, the calculation formula for the required simulation time is: Required simulation time = temperature recovery time - shortest acquisition time.

5. A method for predicting a DTS temperature recovery steady-state curve of a water injection well according to claim 1, characterized in that: In S2, the formula corresponding to the temperature recovery simulation curve model is: and alog b x Among them, y is the recovery temperature, a and b are fitting constants, and x is time.

6. A method for predicting a DTS temperature recovery steady-state curve of a water injection well according to claim 1, characterized in that: The historical measured temperature recovery data is obtained through sampling, and the simulation of the DTS temperature recovery steady-state curve is completed according to the sampling time interval.

7. A method for predicting a DTS temperature recovery steady-state curve of a water injection well according to claim 1, characterized in that: In S3, three parameters, temperature prediction, cut-off time and noise superposition, are added to simulate the DTS temperature recovery steady-state curve.

8. A water injection well DTS temperature recovery steady-state curve prediction system, used to implement the steps of the water injection well DTS temperature recovery steady-state curve prediction method according to any one of claims 1 to 7, characterized in that: include: A data acquisition module is used to acquire historical measured temperature recovery data, and determine the shortest acquisition time and the temperature recovery time when the temperature reaches a steady state according to the historical measured temperature recovery data; The model building module is used to obtain the required simulation time based on the shortest acquisition time and the temperature recovery time, and to build a temperature recovery simulation curve model in combination with the historical measured temperature recovery data; The curve simulation module is used to input the time point corresponding to the required simulation time into the temperature recovery simulation curve model to simulate and form a DTS temperature recovery steady-state curve.

9. A device, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the method for predicting the DTS temperature recovery steady-state curve of an injection well as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, it is used to implement the steps of the method for predicting the DTS temperature recovery steady-state curve of an injection well as described in any one of claims 1 to 7.

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