CN108732621B - FFC-resistivity-based while-drilling fine time depth prediction method - Google Patents

FFC-resistivity-based while-drilling fine time depth prediction method Download PDF

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CN108732621B
CN108732621B CN201810223045.3A CN201810223045A CN108732621B CN 108732621 B CN108732621 B CN 108732621B CN 201810223045 A CN201810223045 A CN 201810223045A CN 108732621 B CN108732621 B CN 108732621B
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resistivity
shale
brine
velocity
depth
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CN108732621A (en
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邓勇
刘仕友
付琛
孙万元
郭伟
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China National Offshore Oil Corp CNOOC
CNOOC China Ltd Zhanjiang Branch
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China National Offshore Oil Corp CNOOC
CNOOC China Ltd Zhanjiang Branch
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
    • G01V1/30—Analysis
    • G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
    • G01V1/30—Analysis
    • G01V1/303—Analysis for determining velocity profiles or travel times
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/60—Analysis
    • G01V2210/61—Analysis by combining or comparing a seismic data set with other data
    • G01V2210/616—Data from specific type of measurement
    • G01V2210/6169—Data from specific type of measurement using well-logging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/60—Analysis
    • G01V2210/62—Physical property of subsurface
    • G01V2210/622—Velocity, density or impedance
    • G01V2210/6222—Velocity; travel time

Abstract

The invention discloses a while-drilling fine time depth prediction method based on FFC-resistivity, which comprises the following steps of: s1, integrating the earthquake and well logging data, and providing an examinationAnd (3) predicting the classification speed by considering the lithology information according to the following formula: vshale＝ashale×LOG10(RTshale×DEPTH)+bshaleAnd calculating a mudstone velocity value, wherein: vshaleIs the mudstone velocity, ashale、bshaleIs the regional mudstone dielectric constant, RTshaleAs mudstone resistivity, LOG10Performing logarithmic operation with 10 as a base, wherein DEPTH is the altitude and DEPTH; s2, integrating the zone log data, and proposing a velocity prediction considering pore fluid information by the following formula: vbrine＝abrine×LOG10(RTbrine×DEPTH)+bbrineAnd calculating the speed of the water-containing sandstone, wherein: vbrineVelocity of saturated sandstonebrine、bbrineIs the medium constant, RT, of the regionally saturated sandstonebrineFor saturated sandstone resistivity, LOG10Performing logarithmic operation with 10 as a base, wherein DEPTH is the altitude and DEPTH; s3, integrating the regional logging information, and providing a sandstone speed prediction method after considering the gas content of the pore fluid: and replacing the resistivity of the gas-containing sandstone by a resistivity fluid to calculate the resistivity of the replaced water sand, calculating the velocity of the replaced water sand longitudinal wave, and replacing by a velocity fluid to calculate the velocity of the gas sand longitudinal wave.

Description

FFC-resistivity-based while-drilling fine time depth prediction method
Technical Field
The invention relates to the technical field of oil and gas exploration, in particular to a while-drilling fine time depth prediction method based on FFC-resistivity.
Background
With the continuous deepening of oil and gas exploration and the continuous improvement of exploration level, the emphasis of marine oil and gas exploration is moving to the fields of deep water, ultra-deep water, high temperature and high pressure and the like, and the exploration in the fields has the outstanding characteristics of high exploration operation cost and high risk. The time-depth relation is accurately predicted in the drilling process, the completion of the fine time-depth stuck layer is beneficial to the drilling decision judgment in the key drilling process, the completion of professional tasks such as casing running and the like, the industrial risk is reduced, and the safety and the economic benefit of personnel are guaranteed. In addition, longitudinal wave velocity data plays a very important role in technical research and application such as reservoir prediction, fluid detection and the like, and is the premise and the basis of AVO analysis, seismic forward modeling and prestack inversion.
However, due to various reasons, the lack of longitudinal wave velocity data of some wells or well sections seriously restricts the precise and deep prediction while drilling, and brings great risk to drilling. Meanwhile, the application of subsequent petrophysical analysis, reservoir prediction technology and fluid detection technology is restricted, so that the development of the longitudinal wave velocity prediction technology with high precision and applicability has important significance for oil and gas exploration and development.
In the aspect of longitudinal wave velocity prediction, researchers have carried out a lot of work, and various prediction technologies are proposed, including various theoretical model methods represented by Xu-White theoretical models, empirical formula methods based on porosity and mud content proposed by Han, Nur and the like, and empirical formula methods based on density curves proposed by Gardner, wherein the theoretical model methods and the empirical formula methods based on Han and the like need to provide accurate mineral and fluid contents, the Gardner formula needs to have density logging curves, but only gamma and resistance logging curves exist in the current partial wells, so that accurate mineral and fluid contents cannot be obtained, the longitudinal wave velocity prediction cannot be carried out by adopting the theoretical model and the empirical formula based on Han and the like, and the Gardner formula cannot carry out prediction according to lithology, and the accurate longitudinal wave velocity cannot be obtained according to the Gardner formula.
Although Faust proposes a formula for predicting the longitudinal wave velocity according to the statistical relationship between the resistivity curve and the longitudinal wave velocity curve, a large amount of statistical analysis on West oil fields in south China sea shows that only the resistivity of the water layer and the mudstone has a good correlation with the longitudinal wave velocity, and the correlation between the longitudinal wave velocity of the oil-gas layer and the resistivity is not obvious, so that the longitudinal wave velocity of the water layer and the mudstone can be well predicted only by directly adopting the Faust formula, and the longitudinal wave velocity of the oil layer and the gas layer cannot be well predicted.
The acoustic jet-lag logging has wide application in the aspects of stratum evaluation, oil deposit description, seismic interpretation and the like. Particularly, the acoustic wave data are used for synthesizing seismic records, so that the seismic data and well logging data can be jointly used, and reservoir parameters can be predicted. The resistivity is usually converted to acoustic waves using the Faust formula, but is not applicable to all formations due to the limitations of the Faust formula itself. In general, different parameters may be selected for different lithologies, but since these parameters are approximations counted by a large amount of data, the selected parameters are not necessarily the optimal parameters for a particular region; even in the same region, the longitudinal wave velocity of the rock is not necessarily the same because of different buried depths and different deposition environments of different strata.
The formation velocity has a more complex relationship with the electrical property and the buried depth, and the relationship between the formation velocity and the resistivity is approximately researched by the Grouer by using a Faust formula; obtaining the change rule between the rock wave velocity and the resistivity and the mutual relation between the rock wave velocity and the resistivity in the fluid displacement process in the stratum state by the xu group circumference under the laboratory condition; various approximate relational formulas of micro-logging speed and inversion resistivity and depth of transient data at the point are studied strictly and perfectly, and the formation speed is fitted by a high-order polynomial of lg (rho) and lg (v), so that better fitting accuracy can be obtained; a test of desert zone surface structure survey is carried out by using a central loop line transient electromagnetic sounding method in the abdominal region of the next-generation Zungang basin.
The Faust's formula characterizes the statistical relationship between the formation resistivity curve and the sonic curve, and is not applicable to all formations because the sonic and resistivity curves, in addition to being affected by lithology, have a greater effect on resistivity than the sonic fluid in the formation. The application condition of the Faust formula is that the resistivity curve and the acoustic curve have a stratum with a good statistical relationship, so that the Faust formula can be utilized to reconstruct the acoustic curve from the resistivity curve under the condition of serious acoustic distortion; in the research area of the Faust formula applicable condition, after the stratum under the same deposition environment is determined, the value of the formula is also determined, the well section under the same deposition environment is selected, and the curve in the data of good quality of the adjacent wells of the same stratum is used for solving through the formula. If the well has good quality data in other well sections of the same type, the curve in the data can be used for solving through a formula.
A large number of statistical analyses indicate that the resistivity of a water layer and mudstone has good correlation with the longitudinal wave velocity, so that a novel resistivity-based longitudinal wave velocity prediction method is provided.
Although Faust proposes a formula for predicting the longitudinal wave velocity according to the statistical relationship between the resistivity curve and the longitudinal wave velocity curve, a large amount of statistical analysis on West oil fields in south China sea shows that only the resistivity of the water layer and the mudstone has a good correlation with the longitudinal wave velocity, and the correlation between the longitudinal wave velocity of the oil-gas layer and the resistivity is not obvious, so that the longitudinal wave velocity of the water layer and the mudstone can be well predicted only by directly adopting the Faust formula, and the longitudinal wave velocity of the oil layer and the gas layer cannot be well predicted.
Faust proposes a formula for predicting the velocity of longitudinal waves according to the statistical relationship between the resistivity curve and the velocity curve of longitudinal waves, but the formula has the current situations of poor application effect and low realization efficiency in West oil fields in the south China sea. A large number of statistical analyses show that the fitting of the resistivity of a water layer and mudstone and the longitudinal wave velocity can be improved by adding the constant term to the empirical formula, and in addition, the logarithmic function relationship of the velocity and the resistivity is provided according to the characteristics of high temperature, high pressure, deep water and other regions in the west of the south sea, so that the fitting precision is further improved. According to the fact that different lithologic fluids have different trends in statistics, a speed prediction idea under lithologic and fluid control is provided. However, researches show that the correlation between the longitudinal wave velocity of a hydrocarbon reservoir and the resistivity is not obvious, so that the longitudinal wave velocity of a water layer and a mudstone can only be well predicted by directly adopting a formula, the longitudinal wave velocity of an oil layer and a gas layer cannot be well predicted, and the hydrocarbon-containing logging section velocity prediction method is provided by combining with a fluid replacement idea. The resistivity prediction speed while drilling under the control of the lithofacies and the fluid can be finely converted in time, the precision is obviously improved compared with that of the traditional method, and the precision requirement in engineering is met.
Disclosure of Invention
The invention provides a while-drilling fine time-depth prediction method based on FFC-resistivity, which has the advantages of wide applicability, high prediction precision, high timeliness, simplicity and easiness in operation, can provide decision-making basis for field layer clamping and casing operation procedures during drilling, reduces the number of drilling operation days, further greatly reduces the exploration operation cost, reduces the safety risk and has inestimable benefit.
In order to solve the technical problem, the embodiment of the application provides a while-drilling fine time-depth prediction method based on FFC-resistivity, which is characterized by comprising the following steps: the method comprises the following steps:
s1, integrating the earthquake and logging data, and providing classification speed prediction considering lithology information by the following formula:
Vshale＝ashale×LOG10(RTshale×DEPTH)+bshaleand calculating a mudstone velocity value, wherein: vshaleIs the mudstone velocity, ashale、bshaleIs the regional mudstone dielectric constant, RTshaleAs mudstone resistivity, LOG10Performing logarithmic operation with 10 as a base, wherein DEPTH is the altitude and DEPTH;
s2, integrating the zone log data, and proposing a velocity prediction considering pore fluid information by the following formula:
Vbrine＝abrine×LOG10(RTbrine×DEPTH)+bbrineand calculating the speed of the water-containing sandstone, wherein:
Vbrinevelocity of saturated sandstonebrine、bbrineIs the medium constant, RT, of the regionally saturated sandstonebrineFor saturated sandstone resistivity, LOG10Performing logarithmic operation with 10 as a base, wherein DEPTH is the altitude and DEPTH;
s3, integrating the regional logging information, and providing a sandstone speed prediction method after considering the gas content of the pore fluid: and replacing the resistivity of the gas-containing sandstone by a resistivity fluid to calculate the resistivity of the replaced water sand, then calculating the velocity of the replaced water sand longitudinal wave, and replacing by a velocity fluid to calculate the velocity of the gas sand longitudinal wave.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
the technology has the advantages of wide applicability, high prediction precision, high timeliness, simplicity and easiness in operation, can provide decision-making basis for field floor clamping, casing operation procedures and the like during drilling, reduces the number of drilling operation days, further greatly reduces the exploration operation cost, simultaneously reduces the safety risk, has immeasurable benefit, and contributes to cost reduction and efficiency improvement of a company.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a technical flow chart of the present invention.
Detailed Description
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
As shown in fig. 1, the fine while-drilling time-depth prediction method based on FFC-resistivity according to the embodiment includes the following steps:
s1, integrating the earthquake and logging data, and providing classification speed prediction considering lithology information by the following formula: vshale＝ashale×LOG10(RTshale×DEPTH)+bshaleAnd calculating a mudstone velocity value, wherein: vshaleIs the mudstone velocity, ashale、bshaleIs the regional mudstone dielectric constant, RTshaleAs mudstone resistivity, LOG10Performing logarithmic operation with 10 as a base, wherein DEPTH is the altitude and DEPTH;
s2, integrating the zone log data, and proposing a velocity prediction considering pore fluid information by the following formula: vbrine＝abrine×LOG10(RTbrine×DEPTH)+bbrineThe velocity of the water-containing sandstone is obtained,wherein: vbrineVelocity of saturated sandstonebrine、bbrineIs the medium constant, RT, of the regionally saturated sandstonebrineFor saturated sandstone resistivity, LOG10Performing logarithmic operation with 10 as a base, wherein DEPTH is the altitude and DEPTH;
s3, integrating the regional logging information, and providing a sandstone speed prediction method after considering the gas content of the pore fluid: and replacing the resistivity of the gas-containing sandstone by a resistivity fluid to calculate the resistivity of the replaced water sand, then calculating the velocity of the replaced water sand longitudinal wave, and replacing by a velocity fluid to calculate the velocity of the gas sand longitudinal wave.
The FFC-based while-drilling resistivity fine time-depth prediction can be completed under the condition of no while-drilling acoustic wave time difference, the underground stratum is finely calibrated, the positions of a drill bit and a target layer are predicted, and a basis is provided for decision-making while drilling. By contrast, the technology has the advantage that the prediction precision is obviously improved in the original prediction technology.
Although the present invention has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (1)

1. A while drilling fine time depth prediction method based on FFC-resistivity is characterized by comprising the following steps: the method comprises the following steps:
s1, integrating the seismic and well logging dataIt is proposed to consider lithology information classification speed prediction by the following formula: vshale＝ashale×LOG10(RTshale×DEPTH)+bshaleAnd calculating a mudstone velocity value, wherein: vshaleIs the mudstone velocity, ashale、bshaleIs the regional mudstone dielectric constant, RTshaleAs mudstone resistivity, LOG10Performing logarithmic operation with 10 as a base, wherein DEPTH is the altitude and DEPTH;
s2, integrating the zone log data, and proposing a velocity prediction considering pore fluid information by the following formula: vbrine＝abrine×LOG10(RTbrine×DEPTH)+bbrineAnd calculating the speed of the water-containing sandstone, wherein: vbrineVelocity of saturated sandstonebrine、bbrineIs the medium constant, RT, of the regionally saturated sandstonebrineFor saturated sandstone resistivity, LOG10Performing logarithmic operation with 10 as a base, wherein DEPTH is the altitude and DEPTH;
s3, integrating the regional logging information, and providing a sandstone speed prediction method after considering the gas content of the pore fluid: and replacing the resistivity of the gas-containing sandstone by a resistivity fluid to calculate the resistivity of the replaced water sand, then calculating the velocity of the replaced water sand longitudinal wave, and replacing by a velocity fluid to calculate the velocity of the gas sand longitudinal wave.
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