A Phase-Controlled Inversion Identification Method for Interbeds in Braided River Reservoirs

Abstract

The present invention discloses a method for phased inversion identification of interbeds in braided river reservoirs, which includes the following steps: Step S10, establishing a geological knowledge base for the study area; calibrating the core according to the geological knowledge base, and quantitatively classifying the electrical characteristics of interbeds with different genetic origins; tracing the distribution of interbeds around the drilled wells; based on the situation of the drilled wells, according to the logging facies analysis, referring to the modern river sedimentation model, and combining with empirical formulas, quantitatively depicting the development scale of sedimentary microfacies in the study area; depicting the distribution pattern of interbeds, comprehensively studying the sedimentary characteristics of the study area, and depicting the advantageous areas for the development of interbeds; inversely calculating the distribution range of interbeds; using the production dynamic data of the study area to test the inversion body to modify and improve the inversion result. The advantages of the present invention are that it provides a simple and accurate method for inversely identifying interbeds in braided river reservoirs. At the same time, this method fully considers the sedimentary background of the study area and provides a basis for the study of interbeds in braided river reservoirs.

Description

Technical Field

[0001] The present invention relates to a method for facies-controlled inversion identification of interbeds in braided river reservoirs, belonging to the field of oil exploration and development. Background Art

[0002] In recent years, the development of most oil fields in China has entered the middle and late stages, and the situation is rather severe. Coupled with the strong heterogeneity of continental reservoirs, it has become increasingly difficult for us to evaluate, exploit and manage oil reservoirs. At this time, relying solely on traditional reservoir description methods can no longer meet the requirements of modern oil field development. People urgently need more refined and effective reservoir description technologies and methods. Reservoir interbeds are one of the main factors causing the heterogeneity of reservoir fluid flow and are also an important part of the fine characterization of reservoirs. The existence of interbeds divides the reservoir body into multiple non-connected or semi-connected flow units, thus controlling the movement of fluids inside the reservoir body. The research on reservoir interbeds has been formed and developed along with the deepening of oil field exploration and development. It is an indispensable research for revealing reservoir heterogeneity, especially for long-term developed oil fields. The formation and distribution of remaining oil are controlled by the genetic types, spatial distributions, etc. of reservoir interbeds. Therefore, carrying out research on reservoir interbeds has important theoretical significance and practical value.

[0003] In traditional methods, there are generally two methods for interbed identification. One is to extract amplitude attributes of seismic horizon slices and display the distribution and boundaries of interbeds by adjusting color scale differences; the other is to trace the waveform changes of seismic profiles and manually depict the distribution of interbeds.

[0004] Both of the above two methods require strong comprehensive knowledge and practical experience in development geology and seismology. Moreover, the workload of manual interpretation is large, and it is difficult to guarantee the accuracy of color scale adjustment and profile tracing. Therefore, the existing technology is difficult to provide a pattern-fitting and highly accurate interbed inversion body to guide the implementation of production wells during the oil field development process. Summary of the Invention

[0005] Aiming at the deficiencies of the existing technology, the present invention provides a method for facies-controlled inversion identification of interbeds in braided river reservoirs. The highlights of this method are threefold: First, by calibrating cores and combining wells with seismic data to establish a seismic forward model, geological reservoir researchers can quantify the development scale of interbeds according to the model; second, the developed interbed pattern proposed by the present invention provides a new idea for depicting interbeds in braided river reservoirs; third, the research results can effectively guide the development of bottom water oil reservoirs in oil fields and guide the deployment of horizontal sections of horizontal wells.

[0006] The technical solution provided by the present invention to solve the above technical problems is: A method for facies-controlled inversion identification of interbeds in braided river reservoirs, comprising the following steps:

[0007] Step S10: Establish a geological knowledge base for the study area. The required data should include the geological background, reservoir characteristics, drilling, logging data, and seismic data of the study area. Integrate the above data to establish a geological knowledge base. The data quality assessment should focus on well-seismic data, observing whether the vertical resolution of seismic data meets the requirements of inversion, whether the logging format standards are unified, and whether other data conforms to geological understanding;

[0008] Step S20: Calibrate the core according to the geological knowledge base, and quantitatively classify the electrical characteristics of interbeds with different origins. A total of four categories are distinguished, namely floodplain muddy interbeds, settling muddy interbeds, channel-through muddy interbeds, and river-bottom lag gravelly interbeds;

[0009] Step S30: Based on the seismic 90° phase-shifted data, combine well and seismic data, and track the distribution of interbeds around the drilled wells according to the change of waveform energy in Petrel software;

[0010] Step S40: Based on the situation of drilled wells, according to logging facies analysis, draw on modern river sedimentation models, and combine with empirical formulas to quantitatively characterize the development scale of sedimentary microfacies in the study area;

[0011] Step S50: Combine Step S40 and the genetic analysis of each interbed and the seismic forward model to characterize the distribution pattern of interbeds, comprehensively study the sedimentary characteristics of the study area, and depict the dominant areas of interbed development;

[0012] Step S60: Based on the seismic 90° phase-shifted data, extract and optimize seismic attributes using Petrel software. Combine the tracking results of Step S30, the dominant areas characterized in Step S40, and the distribution pattern of forward-modeled interbeds in Step S50. Then use the principal component analysis algorithm in Petrel software for multi-attribute fusion to invert the distribution range of interbeds;

[0013] Step S70: Use the production dynamic data of the study area to test the inverted body in Step S60 to modify and improve the inversion results.

[0014] A further technical solution is that the specific process of classification in Step S20 is as follows: First, classify the interbeds in the study area according to their origins through core observation, calibrate the core, and identify and summarize the differences in sedimentary thickness, litho-electric response, etc. of interbeds with different origins. Among them, the floodplain muddy interbed has a thickness of 1 - 10m, gamma of 85 - 130 API, and resistivity of 1 - 2.5 Ω; the settling muddy interbed has a thickness of less than 0.5m, gamma of 70 - 80 API, and resistivity of 2 - 4 Ω; the channel-through muddy interbed has a thickness of 0.5 - 2m, gamma of 75 - 95 API, and resistivity of 2 - 3 Ω; the river-bottom lag gravelly interbed has a thickness of less than 3m, gamma of 90 - 120 API, and resistivity of 5 - 30 Ω.

[0015] A further technical solution is that in the step S30, the tracking process is carried out around the drilled well.

[0016] A further technical solution is that in the step S60, the seismic attributes include amplitude - type, phase - type, and frequency - type attributes. There are two aspects for its preference. One is to compare with the boundary of the dominant area of interbed development qualitatively depicted in the step S50, and the other is to compare with the range of the interbed around the well points tracked in the step S30. After the attributes are preferably selected, when performing multi - attribute fusion, the above two points should also be used to control and constrain the inversion process to improve the accuracy of the inversion result.

[0017] A further technical solution is that in the step S40, the sedimentary microfacies in the study area include point bars and channels.

[0018] A further technical solution is that in the step S70, the production dynamic data in the study area include the water - cut rising rate and the liquid supply volume.

[0019] A further technical solution is that in the step S70, the inspection process is as follows: the water - cut rising rate of the wells deployed within the interbed range should be less than that of the wells deployed outside the interbed range.

[0020] The present invention has the following beneficial effects:

[0021] (1) The present invention is applicable to the work areas with an average well spacing less than 1000 m. If the well spacing is too large, there are two impacts on the inversion effect. First, the accuracy of sedimentary facies characterization is relatively low, and the control effect on inversion is weak; second, the control effect of well - top information on the development of interbeds between wells is weak.

[0022] (2) By establishing seismic forward models of interbeds with different thicknesses, the development scale of interbeds is quantified. The interbed thickness in the study area is between 1 - 3 m, and there are local voids.

[0023] (3) Using core calibration, the litho - electric characteristics of interbeds with different origins are quantified. The thickness of flood - plain argillaceous interbeds is 1 - 10 m, gamma ray is 85 - 130 API, and resistivity is 1 - 2.5 Ω; the thickness of slump argillaceous interbeds is less than 0.5 m, gamma ray is 70 - 80 API, and resistivity is 2 - 4 Ω; the thickness of channel - cut argillaceous interbeds is 0.5 - 2 m, gamma ray is 75 - 95 API, and resistivity is 2 - 3 Ω; the thickness of river - bottom lag gravelly interbeds is less than 3 m, gamma ray is 90 - 120 API, and resistivity is 5 - 30 Ω.

[0024] (4) Compared with the prior art, the present invention introduces the concept of sedimentary facies into the inversion identification of interbeds and establishes a sedimentary pattern of interbeds to constrain the multi - attribute fusion inversion, making the inversion result more geologically significant and more reliable.

[0025] (5) The sandwich inversion method provided by the invention is convenient to operate, has clear conclusions, and practical results, and has strong operability and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a flow chart;

[0027] Figure 2 is a multi-attribute fusion inversion map of mud and conglomerate interbeds;

[0028] Figure 3 is a production characteristic map of Well J53H. DETAILED DESCRIPTION OF THE INVENTION

[0029] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Components of the embodiments of the present invention described and illustrated herein can generally be arranged and designed in a variety of different configurations.

[0030] A phased inversion identification method for interbeds in a braided river reservoir according to the present invention mainly includes the following steps as Figure 1 shown:

[0031] 1. Establish a seismic forward model using the interbeds calibrated in the well.

[0032] In the example area, the reservoir of the Guantao Formation in Oilfield C is a braided river deposit with an average thickness of more than 10 meters, which is a generally connected body as a whole, and interbeds are developed inside the reservoir. Through core calibration, the genetic types of interbeds in the whole area are quantitatively identified, and it is found that a set of stable mud and conglomerate interbeds are developed between the 2nd and 3rd sub-layers of the Guantao Formation, effectively delaying the coning of the bottom water and extending the water-free oil production period. To verify the distribution pattern of this interbed, three sets of seismic forward models are designed in this method.

[0033] First, the model is a constant thickness model. In this model, the interbeds are all composed of gravel and are distributed in the reservoir with a constant thickness of 3m. It can be seen from the geological model of the interbed that the 3m-thick interbed has a strong response in the seismic, but the amplitude loudness of its forward record is significantly stronger than the actual seismic data, indicating that the interbed design of the geological model is thicker than the actual one.

[0034] Second, the model is a gradually varying thickness model. In this model, the interbeds are all composed of gravel and are distributed in the reservoir in a pattern of gradually thickening from 1 m to 3 m. The thickness variation mainly refers to the drilling encounter situation in the exploration well (such as Well 4). It can be seen from the interbed and interlayer geological model that the interbeds with a relatively thin thickness (1 m) will also have a relatively strong seismic response. By superimposing the geological model and the actual seismic data, it is found that the forward modeling seismic amplitude in some areas is stronger than the actual seismic data, indicating that the interbeds in the actual formation are not only composed of gravel, but also contain a considerable amount of mud, which together with the gravel forms this set of interbeds.

[0035] Third, the model is a local cavity model. In the model, the interbeds are composed of gravel and mud, with an interbed thickness ranging from 0 m to 3 m. Local cavities are set in the interbeds, which are composed of sandstone with high porosity and high permeability. It can be seen from the superimposed cross-section of the geological model and the actual seismic data that the forward modeling response at the local cavity is close to the actual seismic data, indicating that this set of interbeds is not "solid as a rock", with a very thin local thickness or even no interbed in some areas, thus forming a seepage channel.

[0036] 2. Establish the interbed development pattern using the drilling encounter information in the well;

[0037] Based on the information such as the thickness, development location, lithology, and well logging curves of the interbeds and interlayers encountered in the well, combined with the seismic forward modeling, the development pattern of the interbeds is depicted.

[0038] Taking Well A21 as an example, a 4.2-m-thick floodplain mud interbed developed between the second and third sub-layers in this well, but no river-bottom lag mud gravel interbed developed. This is because this well developed beach tail sediment in the third sub-layer. Due to the relatively large accommodation space in the later stage, a thick floodplain mud interbed was deposited, and then it was covered by the channel bar sediment of the second sub-layer in the later stage, avoiding being scoured by the channel water flow, so that the interbed was retained. However, since the second sub-layer is channel bar sediment and there is no gravel source, only the floodplain mud interbed developed.

[0039] Taking Well J62 as an example, a 0.9-m-thick river-bottom lag mud gravel interbed developed between the second and third sub-layers in this well, but no floodplain mud interbed developed. This is because this well developed beach head sediment in the third sub-layer. Due to the relatively small accommodation space in the later stage, no thick floodplain mud interbed was deposited, and then it was scoured by the water flow of the second sub-layer channel in the later stage, resulting in the non-development or complete scouring of the mud interbed. However, since the second sub-layer is channel sediment, a thick conglomerate was deposited at the bottom of the channel, so only the river-bottom lag mud gravel interbed developed.

[0040] Judging from Well A36H, a 0.4-m-thick river-bottom lag gravel interbed and a 1.8-m floodplain argillaceous interbed developed between the second and third sub-layers in this well. This is because channel deposits developed in the third sub-layer of this well. Due to the relatively large accommodation space in the later stage, a thick floodplain argillaceous interbed was deposited. Due to the existence of the sand body at the bottom of the second sub-layer, the thick argillaceous layer was retained and not scoured by the channel flow of the second sub-layer. Coupled with the deposition of conglomerate at the bottom of the channel of the second sub-layer, the situation of coexistence of the floodplain argillaceous interbed and the river-bottom lag gravel interbed was formed.

[0041] Judging from Well J61, a 1.5-m-thick river-bottom lag gravel interbed developed between the second and third sub-layers in this well, and no floodplain argillaceous interbed developed. This is because channel deposits developed in the third sub-layer of this well. Due to the relatively large accommodation space in the later stage, a thick floodplain argillaceous interbed was deposited, but due to being scoured by the channel flow of the second sub-layer, it was difficult to retain the thick argillaceous layer. Therefore, only the deposition of conglomerate at the bottom of the channel of the second sub-layer was retained, forming the river-bottom lag gravel interbed.

[0042] Based on the above analysis, mud and conglomerate interbeds developed in the braided channels of the second sub-layer, the channels of the third sub-layer, the beach tails and the beach wings.

[0043] 3. As Figure 2 shown, use seismic attribute fusion inversion to display the distribution of the interbed;

[0044] First, draw the logging microfacies maps of the second and third sub-layers based on the logging facies, superimpose the braided channels of the second sub-layer and the microfacies of the channels, beach tails and beach wings of the third sub-layer, delineate the advantageous areas for the development of the interbed, and use the advantageous areas as constraints to control the seismic attribute fusion inversion.

[0045] Based on the inversion results and the production characteristics of production wells, there are 21 wells (excluding newly put into production wells) in the whole area. Only the production conditions of Well A61H and Well A16H do not match the inversion results, and the coincidence rate reaches 90%. Based on this, combined with the well pattern and the demand for remaining oil tapping potential, a new production well (J53H) was deployed in the area where the interbed developed. This well was put into production at the beginning of May 2022. As of the end of June 2022, it has been in production for about 60 days, with a daily oil production of about 80 cubic meters and a water cut still lower than 20%, and the production effect is good ( Figure 3 ).

[0046] According to the above analysis, the practical effect of the seismic attribute fusion inversion technology based on sedimentary facies constraints is good.

[0047] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, rather than limitations on the implementation manners of the present invention. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to enumerate all implementation manners here. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the claims of the present invention.

Claims

1. A method for facies-controlled inversion and identification of interbeds in braided river reservoirs, characterized in that It includes the following steps: Step S10: Establish a geological knowledge base for the study area; Step S20: Calibrate the core according to the geological knowledge base, and quantitatively classify the electrical characteristics of interbeds with different origins; Step S30: Based on the seismic 90° phase shift data, combine well and seismic data, and in the Petrel software, track the distribution of interbeds around the drilled wells according to the change of waveform energy; Step S40: Based on the situation of drilled wells, according to logging facies analysis, draw on modern river sedimentation models, and combine with empirical formulas to quantitatively characterize the development scale of sedimentary microfacies in the study area; Step S50: Combine Step S40 and the genetic analysis of each interbed and the seismic forward model to characterize the distribution pattern of interbeds, comprehensively study the sedimentary characteristics of the study area, and depict the dominant areas of interbed development; Step S60: Based on the seismic 90° phase shift data, extract and optimize seismic attributes using the Petrel software, combine the tracking results of Step S30, the dominant areas depicted in Step S50, and the distribution pattern of forward-modeled interbeds in Step S50, and then use the principal component analysis algorithm in the Petrel software for multi-attribute fusion to invert the distribution range of interbeds; Step S70: Use the production dynamic data of the study area to test the inversion body in Step S60 to modify and improve the inversion results.

2. The phase-controlled inversion identification method for interbeds in braided river reservoirs according to claim 1, characterized in that The specific process of classification in Step S20 is as follows: First, classify the interbeds in the study area by origin through core observation, calibrate the core, and identify and summarize the differences in sedimentary thickness and litho-electric response of interbeds with different origins; among them, the thickness of floodplain mud interbeds is 1-10m, gamma is 85-130API, and resistivity is 1-2.5Ω; the thickness of slump mud interbeds is less than 0.5m, gamma is 70-80API, and resistivity is 2-4Ω; the thickness of channel-fill mud interbeds is 0.5-2m, gamma is 75-95API, and resistivity is 2-3Ω; the thickness of river-bottom lag gravelly interbeds is less than 3m, gamma is 90-120API, and resistivity is 5-30Ω.

3. A method for phased inversion and identification of interbeds in braided river reservoirs according to claim 1, characterized in that The tracking process in Step S30 is carried out around the drilled wells.

4. A method for phased inversion and identification of interbeds in a braided river reservoir according to claim 1, characterized in that The seismic attributes in Step S60 include amplitude, phase, and frequency attributes.

5. A method for identifying interbeds in braided river reservoirs by phased inversion, according to claim 1, characterized in that The sedimentary microfacies in the study area in Step S40 include point bars and channels.

6. A method for phased inversion identification of interbeds in braided river reservoirs according to claim 1, characterized in that The production dynamic data of the study area in Step S70 include the water cut rising rate and liquid supply volume.

7. A method for identifying interbeds in braided river reservoirs by facies-controlled inversion, as claimed in claim 1, wherein The testing process in Step S70 is: The water cut rising rate of wells deployed within the interbed range should be less than that of wells deployed outside the interbed range.

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