A method for adjusting the trajectory of a horizontal well

Abstract

The present application relates to a kind of horizontal well trajectory adjustment method, belong to oil and gas reservoir exploration and development technical field.The horizontal well trajectory adjustment method of the present application, after horizontal section of horizontal well encounters mudstone, through well logging real drilling data lithology description, while drilling natural gamma and fitting generated neutron data, to the inversion data body is corrected, evaluation and selection, adjust subsequent horizontal section trajectory.The horizontal well trajectory adjustment method of the present application is realized on the basis of design inversion, by means of geophysical prospecting, geology, cooperation simulation inversion etc..The method effectively solves the problem that the quality of seismic data in the study area is good, the degree of well control is high, the reservoir heterogeneity is strong, and the horizontal well encounters mudstone needs to adjust well trajectory, which is of great significance for the development of high degree of area.

Description

Technical Field

[0001] This invention relates to a method for adjusting the trajectory of a horizontal well, belonging to the field of oil and gas reservoir exploration and development technology. Background Technology

[0002] During horizontal well development, due to reservoir heterogeneity, mudstone is often encountered in the horizontal section. The common practice is to re-conduct reservoir prediction and structural analysis based on the actual drilling lithology and structural understanding, and adjust the subsequent trajectory. Reservoir prediction methods mainly include attribute slice extraction and inversion techniques. Attribute slice extraction is a lateral reservoir prediction technique that can predict the planar distribution of the reservoir; inversion techniques can predict the three-dimensional spatial distribution of the reservoir. Incorporating logging data from the mudstone encounter process in the horizontal section of the horizontal well into the inversion process can improve the accuracy of reservoir prediction and the reservoir encounter rate in horizontal wells. For example, Chinese patent application CN103790577B discloses a depth-domain constrained inversion method for virtual vertical wells in horizontal sections. After the horizontal well encounters sand bodies according to the designed trajectory, sampling points are set at equal intervals along the actual drilling trajectory direction of the horizontal section to extract logging data for the horizontal section, forming a virtual vertical well for inversion calculation. By continuously applying horizontal section data to the inversion prediction, the burial depth and thickness changes of the target sand body ahead of the drill bit can be predicted in a timely manner to adjust the trajectory. However, this method has low utilization of horizontal segment data, lacks specificity, makes it difficult to maximize reservoir prediction accuracy, and is complex to operate. Summary of the Invention

[0003] The purpose of this invention is to provide a method for adjusting the trajectory of a horizontal well, which can solve the problem of complex operation when using logging data from the drilling process of a horizontal section of a horizontal well encountering mudstone for inversion.

[0004] To achieve the above objectives, the technical solution adopted by the horizontal well trajectory adjustment method of the present invention is as follows:

[0005] A method for adjusting the trajectory of a horizontal well includes the following steps:

[0006] (1) Drill the horizontal well according to the design trajectory. After the horizontal section of the horizontal well encounters mudstone, obtain the logging data and actual drilling data of the drilled section of the horizontal well. The logging data includes natural gamma data and lithological data.

[0007] (2) Provide logging data of adjacent wells of the horizontal well, the logging data including natural gamma data and compensated neutron data, the logging data being logging data at depths between H1 and H2, where H1 = (H a -50)m, the H a H2 is the depth value of the top surface of the target layer, in meters. b +50)m, the H bThe depth of the bottom surface of the target layer is in meters. The adjacent wells of the horizontal well are vertical wells that have encountered the target layer and completed logging, or directional wells that have encountered the target layer and completed logging.

[0008] Based on the logging data of adjacent wells of the horizontal well, determine the relationship between natural gamma and compensated neutrons in the target interval;

[0009] (3) Based on the relationship between natural gamma and compensated neutrons in the target layer, the compensated neutron data of the horizontal well is obtained using the natural gamma data of the horizontal well.

[0010] (4) Combining the lithological data of the drilled section of the horizontal well and the data of the adjacent wells of the horizontal well, a geological framework model is built. Natural gamma is used as a sensitive parameter for lithological inversion. Compensated neutron data of the adjacent wells of the horizontal well and the compensated neutron data of the horizontal well are used as covariates for co-simulation to obtain multiple inversion data volumes.

[0011] (5) Based on the well logging interpretation results and geological understanding, the inversion data volume that best reflects the lithological change characteristics is selected from the multiple inversion data volumes;

[0012] (6) Adjust the design trajectory of the horizontal well based on the selected inversion data volume.

[0013] The present invention discloses a method for adjusting the trajectory of horizontal wells. After encountering mudstone in the horizontal section of a horizontal well, the method uses lithological descriptions from actual drilling data, natural gamma ray data during drilling, and neutron data generated from fitting data to correct, evaluate, and select the appropriate data for adjusting the trajectory of subsequent horizontal sections. This method is based on a designed inversion and utilizes geophysical, geological, and co-simulation inversion techniques. This method effectively solves the problem of needing to adjust the well trajectory when encountering mudstone in horizontal wells in areas with high-quality seismic data, high well control, and strong reservoir heterogeneity. It is of significant importance for areas with high levels of development.

[0014] It is understood that the target layer refers to the formation layer where the horizontal well whose trajectory is to be adjusted is located.

[0015] Preferably, the actual drilling data includes well depth data, well inclination data, and azimuth data. The well depth data, well inclination data, and azimuth data are mainly used to determine the location and depth information of horizontal wells.

[0016] For ease of operation, preferably, the relationship between the natural gamma and the compensated neutron is linear. Preferably, the linear relationship is determined by a scatter plot of the natural gamma and the compensated neutron. Preferably, the linear relationship is: CNL = a × GR + b, where a > 0, CNL represents the compensated neutron, and GR represents the natural gamma.

[0017] Preferably, when classifying sandstone and mudstone, sandstone is marked as 1 and mudstone as 0.

[0018] Preferably, during lithological inversion, the natural gamma value for sandstone is less than 85 API, and the natural gamma value for mudstone is greater than or equal to 85 API.

[0019] Preferably, during co-simulation, the numerical range of compensated neutrons corresponding to sandstone is less than 20%.

[0020] Preferably, the lithological inversion and co-simulation are performed using Jason inversion software.

[0021] In this invention, the principle for selecting the inversion data body that best reflects the lithological variation characteristics from the multiple inversion data bodies is as follows: ① The provenance direction, reservoir thickness, channel connectivity, and distribution characteristics of sandstone and mudstone layers obtained from the interpretation of each inversion data body are compared with the stratigraphic understanding. The inversion data body with the highest degree of conformity is the preferred inversion data body; ② Verification is performed through subsequent wells. The inversion data body that conforms to or has the highest degree of conformity with the logging interpretation results of the subsequent wells is the preferred inversion data body. In specific implementation, 1-2 subsequent wells can be selected for verification.

[0022] Preferably, the adjustment of the horizontal well's design trajectory begins at the location of the encountered mudstone and continues drilling in the direction of sandstone indicated by the optimized inversion data volume. The principles for adjusting the horizontal well's design trajectory are as follows: during the trajectory adjustment process, attention should be paid to ensuring engineering construction safety, trajectory smoothness, and ensuring that the trajectory falls within the sandstone interpreted by the inversion data volume as much as possible. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating the method for adjusting the trajectory of a horizontal well as an example.

[0024] Figure 2 This is a schematic diagram of the well trajectory of the X-level well designed using the initial inversion data volume in the embodiment;

[0025] Figure 3 This is a schematic diagram showing the result of adjusting the design trajectory of the X horizontal well using the preferred inversion data volume in the embodiment. Detailed Implementation

[0026] The technical solution of the present invention will be further described below with reference to specific embodiments.

[0027] Example

[0028] Taking horizontal well X in a gas well in a certain basin as an example, this horizontal well is located in a mature development area of ​​a gas field in the basin. In the densely populated well network area, 23 adjacent wells have been drilled through the target layer, and the reservoir is highly heterogeneous. Horizontal well X is designed to be located in the Shihezi Group section below the target layer. Both the pilot hole and point A are logged. The designed horizontal section is 1300m long.

[0029] The method for adjusting the horizontal well trajectory in this embodiment is as follows: Figure 1 As shown, the specific steps include:

[0030] (1) Collect well files, model framework and velocity field during the inversion process of the predicted trajectory of the designed horizontal section after the logging of the A target point of horizontal well X is completed;

[0031] The method for designing the well trajectory of a horizontal well X includes the following steps:

[0032] a. Based on data from adjacent wells, construct a geological framework model of horizontal well X, perform inversion, obtain the initial inversion data volume, and determine the sand top of horizontal well X. Figure 2 Geophysical exploration re-predicts sand top and sand bottom ( Figure 2 Geophysical exploration in the middle re-predicts the sand bottom;

[0033] b. Based on the initial inversion data volume, combined with the geological sand top and bottom structure ( Figure 2 The geological re-predicted sand top and sand bottom maps and reservoir thickness maps are used to determine the upper and lower target frames (e.g., for X-level wells) of the X-level well. Figure 2 As shown in the figure, the design trajectory of the X horizontal well is obtained, and the results are as follows. Figure 2 As shown;

[0034] (2) When the horizontal section reached 833m, logging data showed that 122m of gray mudstone was continuously encountered at the bottom of the well. Based on the reservoir prediction results obtained from the initial inversion data volume interpretation (such as...), Figure 2 (As shown) does not match the actual drilling;

[0035] Acquire logging and actual drilling data for the drilled section of horizontal well X. Logging data includes natural gamma ray data and lithological data (such as...). Figure 2 As shown, Figure 2 The medium and coarse sandstone and fine and siltstone in the well are determined by logging data. The actual drilling data includes well depth data, well inclination data and azimuth data. Among them, well depth data, well inclination data and azimuth data are mainly used to calibrate the position and depth information of the X horizontal well in the inversion software, and do not participate in the main inversion process.

[0036] (3) Extract logging data from adjacent wells (23 adjacent wells) of horizontal well X. The logging data includes natural gamma data and compensated neutron data. The logging data is from depths H1 to H2, where H1 = (H a -50)m, H aH2 represents the depth of the top surface of the target layer, in meters. b +50)m, H b This represents the depth of the bottom surface of the target layer, in meters (m).

[0037] The relationship between natural gamma and compensated neutron was determined by scatter plot of natural gamma and compensated neutron: CNL = 0.1723 × GR + 0.021, where CNL represents compensated neutron and GR represents natural gamma.

[0038] Based on the relationship between natural gamma and compensated neutrons, the compensated neutron data of the X horizontal well are obtained using the natural gamma data of the X horizontal well.

[0039] (4) Based on the lithological data of the drilled section of the X horizontal well, the sandstone and mudstone are divided and identified. The sandstone is marked as 1 and the mudstone is marked as 0. The identification column data is obtained. Then the identification column data is loaded into the Jason software in file format. The lithological data of the drilled section of the X horizontal well is added to the inversion software. Combined with the lithological data of the drilled section of the X horizontal well and the data of adjacent wells, a new geological framework model of the X horizontal well is built.

[0040] Based on the new geological framework model, lithology inversion was performed using natural gamma as a sensitive parameter. Compensated neutron data from adjacent wells of the X-level well and the calculated compensated neutron data from the X-level well were used as covariates for co-simulation, resulting in multiple inversion data volumes. During lithology inversion, the natural gamma values ​​for sandstone were less than 85 API, while those for mudstone were greater than or equal to 85 API (the inversion data volumes did not clearly distinguish between sandstone and mudstone types). During co-simulation, the compensated neutron values ​​for sandstone were less than 20%.

[0041] (5) Compare multiple inversion data volumes with the actual drilling data and reservoir understanding of the drilled section of the X horizontal well. Select the inversion data volume that best reflects the lithological variation characteristics from among the multiple inversion data volumes. The results are as follows: Figure 3 As shown; the principle for selecting the optimal inversion data body by comparing multiple inversion data bodies with the actual drilling data and reservoir understanding of the drilled section of the X horizontal well is as follows: ① Compare the source direction, reservoir thickness, channel connectivity, and distribution characteristics of sandstone and mudstone layers obtained from the interpretation of each inversion data body with the stratigraphic understanding, and the inversion data body with the highest degree of conformity is the preferred inversion data body; ② Verify through 1-2 subsequent wells, and the inversion data body that conforms to or has the highest degree of conformity with the logging interpretation results of the subsequent wells is the preferred inversion data body;

[0042] (6) Based on the selected inversion data volume, the sand top of the X horizontal well is redefined. Figure 3 Geophysical exploration re-predicts sand top and sand bottom ( Figure 3Geophysical exploration re-predicts the sand bottom, combined with geological sand top and bottom structures ( Figure 3 In the geological re-predicted sand top and sand bottom maps and reservoir thickness maps, determine the upper and lower target frames (e.g., ...) of the subsequent trajectory of the X-horizontal well. Figure 3 As shown), the design trajectory of horizontal well X was adjusted, and the adjustment result is as follows. Figure 3 As shown; the adjustment principles are as follows: during the trajectory adjustment process, attention should be paid to ensuring the safety of engineering construction, the smoothness of the trajectory, and ensuring that the trajectory falls within the sandstone interpreted by the inverted data volume as much as possible.

Claims

1. A method for adjusting the trajectory of a horizontal well, characterized in that, Includes the following steps: (1) Drill the horizontal well according to the design trajectory. After the horizontal section of the horizontal well encounters mudstone, obtain the logging data and actual drilling data of the drilled section of the horizontal well. The logging data includes natural gamma data and lithological data. (2) Provide logging data of adjacent wells of the horizontal well, wherein the logging data includes natural gamma data and compensated neutron data, wherein the logging data is logging data with a depth between H1 and H2, wherein H1 = (Ha-50)m, wherein Ha is the depth value of the top surface of the target layer in m, wherein H2 = (Hb+50)m, wherein Hb is the depth value of the bottom surface of the target layer in m, and wherein the adjacent wells of the horizontal well are vertical wells that have encountered the target layer and completed logging or directional wells that have encountered the target layer and completed logging; Based on the logging data of adjacent wells of the horizontal well, the relationship between natural gamma and compensated neutrons in the target interval is determined; the relationship between natural gamma and compensated neutrons is linear, and the linear relationship is: CNL=a×GR+b, where a>0, CNL represents compensated neutrons, and GR represents natural gamma; (3) Based on the relationship between natural gamma and compensated neutrons in the target layer, the compensated neutron data of the horizontal well is obtained using the natural gamma data of the horizontal well. (4) Combining the lithological data of the drilled section of the horizontal well and the data of the adjacent wells of the horizontal well, a geological framework model is built. Natural gamma is used as a sensitive parameter for lithological inversion. Compensated neutron data of the adjacent wells of the horizontal well and the compensated neutron data of the horizontal well are used as covariates for co-simulation to obtain multiple inversion data volumes. (5) Based on the well logging interpretation results and geological understanding, the inversion data volume that best reflects the lithological change characteristics is selected from the multiple inversion data volumes; (6) Adjust the design trajectory of the horizontal well based on the selected inversion data volume.

2. The method for adjusting the trajectory of a horizontal well as described in claim 1, characterized in that, During lithological inversion, the natural gamma values ​​for sandstone are less than 85 API, while those for mudstone are greater than or equal to 85 API.

3. The method for adjusting the trajectory of a horizontal well as described in claim 1, characterized in that, During co-simulation, the numerical range of compensated neutrons for sandstone is less than 20%.

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