CN110552694B - Argillaceous dolomite oil reservoir oil well productivity evaluation method considering multi-factor influence - Google Patents
Argillaceous dolomite oil reservoir oil well productivity evaluation method considering multi-factor influence Download PDFInfo
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- 229910000514 dolomite Inorganic materials 0.000 title claims abstract description 50
- 239000010459 dolomite Substances 0.000 title claims abstract description 50
- 239000003129 oil well Substances 0.000 title claims abstract description 49
- 238000011156 evaluation Methods 0.000 title description 2
- 230000035699 permeability Effects 0.000 claims abstract description 60
- 230000035945 sensitivity Effects 0.000 claims abstract description 39
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- 238000004445 quantitative analysis Methods 0.000 claims abstract description 8
- 239000003921 oil Substances 0.000 claims description 113
- 238000006073 displacement reaction Methods 0.000 claims description 25
- 239000010779 crude oil Substances 0.000 claims description 22
- 239000011435 rock Substances 0.000 claims description 15
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Abstract
The invention provides a method for evaluating the productivity of a argillaceous dolomite oil reservoir oil well by considering multi-factor influence. The method mainly comprises the following steps: acquiring basic parameters of a target argillaceous dolostone oil reservoir; obtaining a relation equation of core permeability and stress through a core stress sensitivity experiment, and establishing a target argillaceous dolomite oil reservoir permeability change model considering stress sensitivity based on the relation equation of the core permeability and the stress; establishing a steady-state seepage model considering starting pressure; establishing a target argillaceous dolomite oil reservoir oil well productivity evaluation model considering multi-factor influence according to the permeability change model and the steady-state seepage model considering the starting pressure; and predicting the productivity change of the oil well by adopting a quantitative analysis method according to the target argillaceous dolomite oil reservoir oil well productivity evaluation model. The method can be used for predicting the permeability distribution of the argillaceous dolomite oil deposit with the stress sensitive effect and the starting pressure gradient and evaluating the productivity of the oil well, and has guiding significance for the development of the argillaceous dolomite oil deposit.
Description
Technical Field
The invention relates to the technical field of oil and gas reservoir development, in particular to a method for evaluating the oil well productivity of a argillaceous dolomite oil reservoir by considering multi-factor influence.
Background
As oil and gas exploration and development progresses, exploration and development goals have begun to develop gradually from the conventional oil and gas field to the unconventional new field. Argillaceous dolomite oil reservoirs are receiving increasing attention as a reserve with great potential. As with ordinary low permeability fields, the development of argillaceous dolomitic reservoirs is often accompanied by stress-sensitive effects. Fatt and Davis initially study the permeability stress sensitivity characteristics of reservoir rocks and propose reservoir stress sensitivity for the first time, and a large number of studies in recent years show that low permeability reservoirs generally have stronger stress sensitivity, and the lower the permeability of reservoir rocks, the stronger the stress sensitivity of reservoir rocks. Along with the continuous exploitation of oil and gas, the effective stress borne by reservoir pressure rock is gradually increased, and the pore throat serving as a fluid seepage channel generates certain compression deformation under the action of the effective stress, so that the permeability of reservoir rock is reduced. The presence of stress sensitivity greatly affects well productivity and reservoir ultimate recovery. In addition, the initiation pressure gradient is another important factor affecting the productivity of a hydrocarbon well, and formation fluid can only flow when the pressure gradient is greater than a certain threshold value, which is referred to as the initiation pressure gradient. The argillaceous dolomite oil reservoir has a stress sensitive effect and a large starting pressure, which causes great obstruction to the development of the argillaceous dolomite oil reservoir. Particularly, the permeability of the reservoir changes along with the change of the stress, so that the productivity of the oil well changes, and the research on the analysis technology of the change rule of the permeability of the argillaceous dolomite oil reservoir and the change rule of the productivity of the oil well is particularly important.
Disclosure of Invention
The invention aims to solve the technical problems of the analysis technology of the change rule of the permeability of the argillaceous dolomite rock oil reservoir and the change rule of the oil well productivity, which cannot be solved by the prior art, and provides the method for evaluating the oil well productivity of the argillaceous dolomite rock oil reservoir by considering the influence of multiple factors.
The invention is realized by the following technical scheme: a method for evaluating the productivity of a argillaceous dolomite oil reservoir oil well in consideration of multi-factor influence comprises the following steps:
step 1: acquiring basic parameters of a target argillaceous dolostone oil reservoir;
step 2: obtaining a relation equation of core permeability and stress through a core stress sensitivity experiment, and establishing a target argillaceous dolomite oil reservoir permeability change model considering stress sensitivity based on the relation equation of core permeability and stress;
and step 3: obtaining a starting pressure gradient value of the target argillaceous dolomite oil reservoir through a core displacement experiment, and establishing a steady-state seepage model considering starting pressure;
and 4, step 4: establishing a target argillaceous dolomite oil reservoir oil well productivity evaluation model considering multi-factor influence according to the permeability change model and the steady-state seepage model considering the starting pressure;
and 5: and predicting the productivity change of the oil well by adopting a quantitative analysis method according to the target argillaceous dolomite oil reservoir oil well productivity evaluation model.
In a preferred embodiment of the present invention, in step 1, the basic parameters of the argillaceous dolomitic reservoir include: permeability under original stress conditions of the oil reservoir, reservoir pressure under original conditions of the oil reservoir, reservoir boundary radius, wellbore radius, reservoir crude oil viscosity, reservoir crude oil volume coefficient, and reservoir thickness.
In a preferred embodiment of the present invention, the permeability of the oil reservoir under the original stress condition is tested by gas measurement and liquid measurement respectively; the oil reservoir pressure and the oil reservoir boundary radius under the original oil reservoir condition are obtained by adopting a well testing analysis method; the oil reservoir thickness is obtained by a logging method; the viscosity of the crude oil in the oil reservoir and the volume coefficient of the crude oil in the oil reservoir are obtained by adopting a sampling analysis test method.
In a preferred embodiment of the present invention, in the step 2, the core stress sensitivity experiment is performed by using a displacement mode of constant confining pressure and variable displacement pressure, and the variation of the displacement pressure is realized by changing the displacement speed, wherein the displacement speed is controlled to be 0.05cm3/min-2.0cm3/min。
In a preferred embodiment of the present invention, in the step 2, the permeability and stress of the core conform to an exponential relationship, and the equation of the relationship between permeability and stress is:
wherein k is the permeability of different positions of the oil reservoir, and is mum2；k0Permeability at original stress condition of oil reservoir, μm2；p0For the original condition of oil reservoirReservoir pressure, MPa; p is the pressure of different positions of the oil reservoir, MPa; alpha is alphakIs stress sensitive coefficient, MPa-1。
In a preferred embodiment of the present invention, in the step 2, the permeability change model is:
wherein k is the permeability of different positions of the oil reservoir, and is mum2；k0Permeability at original stress condition of oil reservoir, μm2；p0The reservoir pressure is MPa under the original reservoir condition; p is a radical ofwfBottom hole pressure, MPa; alpha is alphakIs stress sensitive coefficient, MPa-1；reAnd rwRespectively the radius of the oil reservoir boundary and the radius of a shaft, m; r is the radius, m, of different locations of the reservoir.
In a preferred embodiment of the present invention, in the step 3, the steady-state seepage model considering the starting pressure is:
wherein k is the permeability of different positions of the oil reservoir, and is mum2(ii) a p is the pressure of different positions of the oil reservoir, MPa; r is the radius m of different positions of the oil reservoir; mu is the viscosity of the crude oil, mPa.s; lambda is starting pressure gradient, MPa/m; nu is seepage velocity, m/s.
In a preferred embodiment of the present invention, in the step 4, the model for evaluating the productivity of the oil well of the target argillaceous dolomite oil reservoir is:
wherein: q is the single well production, m3/d，k0Permeability at reservoir original stress conditions, μm2；p0And pwfRespectively reservoir original conditionsLower reservoir pressure and bottom hole pressure, MPa; alpha is alphakIs stress sensitive coefficient, MPa-1；reAnd rwRespectively the radius of the oil reservoir boundary and the radius of a shaft, m; r is the radius m of different positions of the oil reservoir; lambda is starting pressure gradient, MPa/m; mu is the viscosity of the crude oil, mPa.s; b is0Is the volume coefficient of crude oil; h is the reservoir thickness, m.
In a preferred embodiment of the present invention, in the step 5, the predicting the oil well productivity change by using the quantitative analysis method includes: influence of stress sensitivity coefficient on oil well productivity; starting the influence of the pressure gradient on the productivity of the oil well; the influence of stress sensitivity and starting pressure gradient on the productivity of the oil well; stress sensitivity and the influence of the starting pressure gradient on the unimpeded flow.
The advantages of the physical model of the invention at least include:
(1) a displacement mode of constant confining pressure and variable displacement pressure is adopted to carry out a core stress sensitivity experiment to test a stress sensitivity coefficient, and the change of the displacement pressure is realized by changing the displacement speed. Compared with the conventional test mode of changing the constant displacement pressure into the confining pressure, the test mode is safer and more reliable, the pressure is difficult to control in the process of increasing the confining pressure, and the experiment failure is caused when the confining pressure exceeds the rock core crushing pressure.
(2) A permeability change model of the argillaceous dolomitic rock oil reservoir is deduced based on oil reservoir engineering and a seepage mechanics theory, the permeability change model can be used for predicting the permeability change of the oil reservoir, and a foundation is provided for the subsequent productivity change prediction.
(3) The method has the advantages that the productivity evaluation model of the oil well of the argillaceous dolomite oil reservoir is established, the productivity change of the oil well is predicted by the model through a quantitative analysis method, and the method has important guiding significance for the development of the argillaceous dolomite oil reservoir.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 illustrates basic parameters of a argillaceous dolomite reservoir according to an embodiment of the present invention;
FIG. 3 is a planar radial flow model of an embodiment of the present invention;
FIG. 4 is a result of the permeability distribution of a argillaceous dolomitic rock reservoir according to an embodiment of the present invention;
FIG. 5 is a graph illustrating the effect of stress sensitivity on throughput in accordance with an embodiment of the present invention
FIG. 6 is a graph illustrating the effect of initiating a pressure gradient on throughput, in accordance with an embodiment of the present invention;
FIG. 7 is a graph illustrating the effect of stress sensitivity and start-up pressure gradients on throughput in accordance with an embodiment of the present invention;
FIG. 8 is a graph illustrating the effect of stress sensitivity and actuation pressure gradients on unimpeded flow in accordance with an embodiment of the present invention;
Detailed Description
The technical scheme of the method for evaluating the oil well productivity of the argillaceous dolomite oil reservoir considering the influence of multiple factors is clearly described in detail in the following by combining the accompanying drawings.
FIG. 1 is a flow chart of a method for evaluating the productivity of a argillaceous dolomite oil reservoir oil well in consideration of multi-factor influence, which specifically comprises the following steps:
step 1: acquiring basic parameters of a target argillaceous dolostone oil reservoir;
step 2: obtaining a relation equation of core permeability and stress through a core stress sensitivity experiment, and establishing a target argillaceous dolomite oil reservoir permeability change model considering stress sensitivity based on the relation equation of core permeability and stress;
and step 3: obtaining a starting pressure gradient value of the target argillaceous dolomite oil reservoir through a core displacement experiment, and establishing a steady-state seepage model considering starting pressure;
and 4, step 4: establishing a target argillaceous dolomite oil reservoir oil well productivity evaluation model considering multi-factor influence according to the permeability change model and the steady-state seepage model considering the starting pressure;
and 5: and predicting the productivity change of the oil well by adopting a quantitative analysis method according to the target argillaceous dolomite oil reservoir oil well productivity evaluation model.
FIG. 2 is a diagram of basic parameter values for a target argillaceous dolomitic reservoir, wherein the permeability of the reservoir under original stress conditions is tested by gas and liquid measurements, respectively; acquiring the oil reservoir pressure and the oil reservoir boundary radius under the original oil reservoir condition by adopting a well testing analysis method; the oil reservoir thickness is obtained by a logging method; the viscosity of the crude oil in the oil reservoir and the volume coefficient of the crude oil in the oil reservoir are obtained by adopting a sampling analysis test method; the stress sensitivity coefficient is obtained by adopting a rock core stress sensitivity experiment; the starting pressure was obtained using a core displacement experiment.
The core stress sensitivity experiment is carried out in a displacement mode of constant confining pressure and variable displacement pressure, the displacement pressure is changed by changing the displacement speed, and the displacement speed is controlled at 0.05cm3/min-2.0cm3And/min. Compared with a conventional test mode that the constant displacement pressure is changed into the confining pressure, the test mode is safer and more reliable, the pressure is difficult to control in the process of increasing the confining pressure, and the experiment failure is caused when the confining pressure exceeds the rock core crushing pressure.
The core permeability and stress obtained by a core stress sensitivity experiment accord with an exponential relation, and the relation equation of the permeability and the stress is as follows:
wherein k is the permeability of different positions of the oil reservoir, and is mum2；k0Permeability at original stress condition of oil reservoir, μm2；p0The reservoir pressure is MPa under the original reservoir condition; p is the pressure of different positions of the oil reservoir, MPa; alpha is alphakIs stress sensitive coefficient, MPa-1。
Assuming that the crude oil flow is a steady state darcy flow, a planar radial flow model is shown in fig. 3. The pressure distribution and theoretical yield of the oil well can be obtained by a pressure distribution and plane radial flow yield formula as follows:
wherein: q is single well production, m3/d，k0For permeability of reservoir under original stress conditionRate, μm2；p0And pwfRespectively the reservoir pressure and the bottom hole pressure under the original condition of a reservoir stratum, namely MPa; p is the pressure of different positions of the oil reservoir, MPa; r iseAnd rwRespectively the radius of the oil reservoir boundary and the radius of a shaft, m; r is the radius m of different positions of the oil reservoir; mu is the viscosity of the crude oil, mPa.s; b is0Is the volume coefficient of crude oil; h is the reservoir thickness, m.
The change model of the permeability of the argillaceous dolomite reservoir can be obtained by combining a relation equation of the permeability and the stress, a plane radial flow yield formula and the pressure distribution of the oil well, and is as follows:
wherein k is the permeability of different positions of the oil reservoir, and is mum2；k0Permeability at original stress condition of oil reservoir, μm2；p0The reservoir pressure is MPa under the original reservoir condition; p is a radical ofwfBottom hole pressure, MPa; alpha is alphakIs stress sensitive coefficient, MPa-1；reAnd rwRespectively the radius of the oil reservoir boundary and the radius of a shaft, m; r is the radius, m, of different locations of the reservoir.
By combining the characteristics of the argillaceous dolomite oil reservoir, the production pressure difference is assumed to be 10MPa, the radius of the oil well is assumed to be 0.15m, and the basic parameters of the oil reservoir are shown in figure 2. The permeability distribution condition of the argillaceous dolomite reservoir obtained by the permeability distribution model is shown in fig. 4, and the result shows that the permeability changes in a funnel-shaped distribution, mainly showing that the permeability loss of a near well zone is very serious, and the permeability loss of a far well zone is relatively small.
The steady state seepage model considering the starting pressure is:
wherein k is the permeability of different positions of the oil reservoir, and is mum2(ii) a p is the pressure of different positions of the oil reservoir, MPa; r is the radius m of different positions of the oil reservoir;mu is the viscosity of the crude oil, mPa.s; lambda is starting pressure gradient, MPa/m; nu is seepage velocity, m/s.
Substituting the change model formula of the permeability of the argillaceous dolomite oil reservoir into a steady-state seepage model considering the starting pressure, and replacing the fluid speed with the yield to obtain:
order to
Then there are:
the above equation is a non-homogeneous first-order linear differential equation, whose general solution is:
integrating to obtain A (r) and then determining the outer boundary condition
The pressure distribution is obtained by substituting the above formula and taking the logarithm of both sides of A (r):
let r be rwThe yield of the production well wall can be obtained, and the yield evaluation model of the oil well of the argillaceous dolomite oil reservoir considering the multi-factor influence can be obtained by converting the engineering unit system to the ground:
wherein: q is the single well production, m3/d，k0Permeability at reservoir original stress conditions, μm2；p0And pwfRespectively the reservoir pressure and the bottom hole pressure under the original condition of a reservoir stratum, namely MPa; alpha is alphakIs stress sensitive coefficient, MPa-1；reAnd rwRespectively the radius of the oil reservoir boundary and the radius of a shaft, m; r is the radius m of different positions of the oil reservoir; lambda is starting pressure gradient, MPa/m; mu is the viscosity of the crude oil, mPa.s; b is0Is the volume coefficient of crude oil; h is the reservoir thickness, m.
Based on a argillaceous dolomite oil reservoir oil well productivity evaluation model considering multi-factor influence, the method for predicting the oil well productivity change by adopting a quantitative analysis method comprises the following steps: influence of stress sensitivity coefficient on oil well productivity; starting the influence of the pressure gradient on the productivity of the oil well; the influence of stress sensitivity and starting pressure gradient on the productivity of the oil well; stress sensitivity and the influence of the starting pressure gradient on the unimpeded flow.
Fig. 5 is a graph of bottom hole flow pressure versus rate of change of production when only stress sensitivity is considered, and it can be seen that the productivity of a single well considering stress sensitivity is significantly lower than that of a single well not considering stress sensitivity, and the difference between the two gradually increases as the bottom hole flow pressure decreases.
Fig. 6 is a relationship between bottom hole flowing pressure and production rate change when only the starting pressure gradient is considered, and it can be seen that the single well productivity considering the starting pressure gradient is obviously lower than the productivity not considering the starting pressure gradient, and the difference amplitude between the two gradually increases with the increase of the bottom hole flowing pressure, which indicates that the influence of the starting pressure gradient must be considered in the actual development process.
Fig. 7 shows the influence of the stress sensitivity and the start-up pressure gradient on the productivity at the same time, when the stress sensitivity and the start-up pressure gradient exist at the same time, the influence on the yield is more serious, and the influence of the stress sensitivity coefficient and the magnitude of the start-up pressure gradient on the reduction amplitude of the yield is very obvious.
Fig. 8 shows the influence of the stress-sensitive and starting pressure gradients on the unimpeded flow, which is also very obvious due to the existence of the stress-sensitive and starting pressure gradients, and the unimpeded flow is gradually reduced with the increase of the stress-sensitive coefficient, and the larger the starting pressure gradient is, the smaller the unimpeded flow is.
The influence of different factors on the productivity of the argillaceous dolomite oil reservoir under different conditions is shown in the figures 5 to 8, and before the oil reservoir is actually exploited, the productivity of the oil well can be predicted according to the oil reservoir geological condition and the argillaceous dolomite oil reservoir oil well productivity evaluation model considering the multi-factor influence, which is provided by the invention, so that the production is guided.
The above description is only an exemplary embodiment of the present invention, and is not intended to limit the scope of the present invention. Any equivalent changes and modifications that can be made by one skilled in the art without departing from the spirit and principles of the invention should fall within the protection scope of the invention.
Claims (8)
1. The method for evaluating the productivity of the oil well of the argillaceous dolomite rock by considering the influence of multiple factors is characterized by comprising the following steps of:
step 1: acquiring basic parameters of a target argillaceous dolostone oil reservoir;
step 2: obtaining a relation equation of core permeability and stress through a core stress sensitivity experiment, and establishing a target argillaceous dolomite oil reservoir permeability change model considering stress sensitivity based on the relation equation of core permeability and stress;
and step 3: obtaining a starting pressure gradient value of the target argillaceous dolomite oil reservoir through a core displacement experiment, and establishing a steady-state seepage model considering starting pressure;
and 4, step 4: establishing a target argillaceous dolomite oil reservoir oil well productivity evaluation model considering multi-factor influence according to the permeability change model and the steady-state seepage model considering the starting pressure; the permeability change model is as follows:
wherein k is the permeability of different positions of the oil reservoir, and is mum2；k0Permeability at original stress condition of oil reservoir, μm2；p0The reservoir pressure is MPa under the original reservoir condition; p is a radical ofwfBottom hole pressure, MPa; alpha is alphakIs stress sensitive coefficient, MPa-1；reAnd rwRespectively the radius of the oil reservoir boundary and the radius of a shaft, m; r is the radius of different positions of the oil reservoir, m;
and 5: and predicting the productivity change of the oil well by adopting a quantitative analysis method according to the target argillaceous dolomite oil reservoir oil well productivity evaluation model.
2. The method for evaluating oil well productivity of argillaceous dolomite oil reservoirs considering multi-factor influence as claimed in claim 1, wherein in step 1, the basic parameters of the standard argillaceous dolomite oil reservoir include: permeability under original stress conditions of the oil reservoir, reservoir pressure under original conditions of the oil reservoir, reservoir boundary radius, wellbore radius, reservoir crude oil viscosity, reservoir crude oil volume coefficient, and reservoir thickness.
3. The method for evaluating the oil well productivity of the argillaceous dolomite rock according to claim 2, wherein the permeability of the reservoir under the original stress condition is respectively tested by adopting a gas test mode and a liquid test mode; the oil reservoir pressure and the oil reservoir boundary radius under the original oil reservoir condition are obtained by adopting a well testing analysis method; the oil reservoir thickness is obtained by a logging method; the oil reservoir crude oil viscosity and the oil reservoir crude oil volume coefficient are obtained by adopting a sampling analysis test method.
4. The method for evaluating the productivity of the oil well of the argillaceous dolomite rock according to the claim 3, wherein in the step 2, the core stress sensitivity test is performed by adopting a displacement mode of constant confining pressure and variable displacement pressure, the variation of the displacement pressure is realized by changing the displacement speed, and the displacement speed is controlled to be 0.05cm3/min-2.0cm3/min。
5. The method for evaluating the productivity of a argillaceous dolomite oil reservoir well considering the multi-factor influence as claimed in claim 4, wherein in the step 2, the permeability of the core and the stress are in an exponential relation, and the relation equation of the permeability and the stress is as follows:
wherein k is the permeability of different positions of the oil reservoir, and is mum2；k0Permeability at original stress condition of oil reservoir, μm2；p0The reservoir pressure is MPa under the original reservoir condition; p is the pressure of different positions of the oil reservoir, MPa; alpha is alphakIs stress sensitive coefficient, MPa-1。
6. The method for evaluating the productivity of a mudstone oil reservoir well considering the multi-factor influence according to claim 5, wherein in the step 3, the steady-state seepage model considering the starting pressure is as follows:
wherein k is the permeability of different positions of the oil reservoir, and is mum2(ii) a p is the pressure of different positions of the oil reservoir, MPa; r is the radius m of different positions of the oil reservoir; mu is the viscosity of the crude oil, mPa.s; lambda is starting pressure gradient, MPa/m; nu is seepage velocity, m/s.
7. The method for evaluating the productivity of the argillaceous dolomite oil reservoir well considering the multi-factor influence according to claim 6, wherein in the step 4, the target argillaceous dolomite oil reservoir well productivity evaluation model is as follows:
wherein: q is the single well production, m3/d，k0For reservoir original stress conditionsPermeability of (d) in μm2；p0And pwfRespectively the reservoir pressure and the bottom hole pressure under the original condition of a reservoir stratum, namely MPa; alpha is alphakIs stress sensitive coefficient, MPa-1；reAnd rwRespectively the radius of the oil reservoir boundary and the radius of a shaft, m; r is the radius m of different positions of the oil reservoir; lambda is starting pressure gradient, MPa/m; mu is the viscosity of the crude oil, mPa.s; b is0Is the volume coefficient of crude oil; h is the reservoir thickness, m.
8. The method for evaluating the productivity of a mudstone oil reservoir well taking the multi-factor influence into consideration according to any one of claims 1 to 7, wherein the step 5 of predicting the change of the productivity of the well by using a quantitative analysis method comprises the following steps: influence of stress sensitivity coefficient on oil well productivity; starting the influence of the pressure gradient on the productivity of the oil well; the influence of stress sensitivity and starting pressure gradient on the productivity of the oil well; stress sensitivity and the influence of the starting pressure gradient on the unimpeded flow.
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