RU2350739C2 - Method of distribution of oil withdrawal between blower and gas-lift wells - Google Patents

Abstract

FIELD: oil and gas industry.

SUBSTANCE: invention refers to oil and gas industry, particularly to process of optimal withdrawal of production from wells operated by blowing and gas-lift methods. The essence of the invention is like follows: the method consists in measurement of technological parameters of wells such as gas consumption, oil yield, buffer pressure, watering, in conversion of parameters and processing, then in building static models of a well, in experimental investigation of process parameters of the well, in checking model adequacy; in development of algorithms of oil withdrawal distribution between wells. By regulating diameters of connecting branches such mode of well operation is established that the total oil yield of concrete blowers and gas-lift wells will satisfy a required production quota for oil withdrawal for a group of wells or for oil field cluster. Also the sum of actual gas consumption for blowers and working gas for gas-lift separate wells is reduced to a minimum providing trouble-free operation of wells and not allowing process troubles on them.

EFFECT: increased efficiency of method due to optimisation of operation modes of blowers and gas-lift wells.

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Description

The invention relates to the oil and gas industry, in particular to the process of optimal selection of products from wells operated by fountain and gas lift methods.

The purpose of the invention is to increase the efficiency of the methods by selecting the optimal operating modes of fountain and gas lift wells

A known method of optimizing the operation of a system of gas lift wells [RF patent No. 93029822, IPC ЕВВ 43/00], where to implement the method measure the technological parameters of the interacting wells, change their technological modes and repeat the operation of determining technological modes to achieve the optimal operation of the interacting wells. The total oil production is measured for separate groups of interacting wells at different gas flow rates for each individual well, the dependence of the total oil production on the change in gas flow rate for the i-th well is determined, technological conditions for each gas-lift well are selected and changed by maximizing the arithmetic average dependencies of the total production oil of interacting wells from gas consumption in individual wells, then the total oil production is measured and compared with the previous value optimization phase as long as the value of oil production growth in the group of interacting wells will not be less than the measurement error of well production. With a limited gas resource, you can turn off wells in descending order of their unit costs. When redistributing the gas resource, you can turn off the wells in descending order of their unit costs. When redistributing the gas resource between groups of interacting wells, it is established by the equality of deviations of the changes in the total oil production obtained with the optimal gas distribution to the change in gas resource for this group of wells.

However, the known method does not provide optimization of operating modes of fountain wells. And also, when optimizing the operating modes of gas-lift groups of wells, the total total gas consumption in the wells (with a limited resource of the working agent - working gas) and the implementation of the plan (which requires the maximum oil production in the field) for production are not minimized.

A known method of optimizing the operation of a system of gas lift wells [RF patent No. 2081301, IPC ЕВВ 43/00], where to implement the method, measure the technological parameters of the interacting wells, change their technological modes and repeat the process of determining the technological modes to achieve the optimal operation of the interacting wells. The total oil production is measured by a system of interacting wells and the gas flow rate is changed at each of the optimized wells and the dependence of oil production on the flow rate change is determined at each well. The total oil production for individual groups of interacting wells is measured at various values of gas flow in individual wells. The dependence of the total oil production on the change in gas flow rate for each of the interacting wells is determined. Technical regimes are selected and changed at each gas-lift well by maximizing the arithmetic average of the total oil production of the interacting wells from gas consumption in individual wells. Then measure the total oil production and compare it with the value at the previous stage of optimization until the oil increase is ensured for a group of interacting wells. With a limited gas resource, you can turn off wells in descending order of their unit costs. When redistributing the gas resource between groups of interacting wells, it can be established by the equality of deviations of the changes in the total oil production obtained at the optimal gas distribution to the change in gas resource for this group of wells.

However, the known method of optimizing the operation of a system of gas lift wells does not allow solving the joint problem of optimizing the operating modes of fountain and gas lift wells. It is known that in the fields the well is usually operated in a gas-lift and fountain way (even in depleted fields there are fountain wells). In this case, the method does not allow solving optimization problems for all wells (fountain and gas lift) and solving the problems of distributing optimal settings between the wells of the fields.

When operating wells under optimal conditions, it is difficult to ensure a plan for oil production in the entire field. Therefore, it seems necessary to consider the problem of the optimal redistribution of oil withdrawals between wells of a given stock, which ensures a minimum of the total actual consumption of associated gas, taking into account the requirements for fulfilling the oil production plan, as well as technological restrictions determined by the allowable selection range (corresponding to the diameters of the nozzles). In addition, in the field conditions during the operation of wells there are various violations and malfunctions, including the failure of wells, stopping them for repair. In such cases, the plan for oil production, of course, will be impossible to fulfill. Therefore, the load of those wells that are stopped for various reasons must be distributed between other wells.

To solve the general task of controlling the technological processes of oil wells of the oil fields NP-1 and NP-2, a hierarchically multi-level integrated distributed information and control system (IMS) has been created, which allows covering the whole range of technological processes based on modern computing, microprocessor technology and telecommunications.

The multilevel distributed IMS covers 43 technological facilities of different levels of the oil fields NP-1 and NP-2, hierarchically observing the principles of priority. The implementation of the algorithm for the optimal distribution of oil production sampling between wells is carried out by local systems of monitoring and control of oilfield technological objects (lower level systems) that are identical in architectural structure. The lower level of the information-management system consists of the “field” level and the level of the controllers - “ARAZ” terminals.

The "field" level of the system covers technological processes at the level of oil clusters equipped with primary sensors and converters, actuators, a set of technical means of communication circuits for data exchange (dedicated physical line, dedicated telephone line, radio channel, switched telephone line, radio station, modems, etc. .d.). The level of controllers consists of the ARAZ control terminals operating with the SCADA ARAZ operating system of the lower level. In lower-level systems in real time, the following tasks are solved:

- interrogation and collection of information of all kinds (analog, discrete, frequency, digital, etc.);

- primary processing of all types of signals;

- implementation of technological and emergency protection;

- calculation of parameters necessary for process control;

- control of technological parameters;

- process control (issuing control actions on actuators);

- collection and control of technological information from technical equipment of other manufacturers (for example, from the POTOK-ZM measuring system);

- information transfer to the upper level and to remote objects (modem, radio and wired);

- automatic download of software to turn on the power and after failures;

- local optimization of operational parameters of wells and other technological processes;

- optimal distribution of oil withdrawals between groups of oil well wells, etc.

As already noted, ARAZ intelligent terminals were used to create a system for monitoring and controlling the technological processes of oil clusters. They are designed for reliable operation in harsh climatic conditions. The terminals do not require strict requirements for operating conditions, namely:

- does not require special boxes, rooms and cabinets, special protection against dust, humidity;

- does not require ventilation and heating;

- there is the possibility of installing terminals in cabinets located on open industrial sites;

- high performance can include a wide operating temperature range (minus 50 ° C - plus 85 ° C).

All technological processes of oil clusters and technological equipment TsPS-1 and TsPS-2 are controlled using the created supervisory control and management system TsPS-1 and TsPS-2 (mid-level systems).

At the level of supervisory control and management of TsPS-1 and TsPS-2, all technological processes of oil clusters are covered and the following tasks are solved:

- operational display of the state of objects;

- operational management of the facility;

- visualization of information in the form of mnemonic diagrams, graphs, tables, dynamic trends, histograms;

- archiving information and a deep archive;

- report generation, report printing (programmatically or at the request of the system operator);

- alarm (sound signals, report, alarms);

- optimal distribution of oil withdrawals between wells, operational change of settings, system diagnostics and performance of design tasks;

- remote interactive dialogue work, which simplifies maintenance;

- loading and unloading of embedded programs via communication channels, database and parameters, etc.

As you know, there is a local approach that provides a minimum of specific gas consumption (for each well), corresponding to the production of 1 ton of oil; in the event that in this case the total production volume provides the required planned target, the problem is solved, otherwise there is a need for an optimal distribution of this planned target between the wells according to the criterion of the minimum total associated gas extraction (working gas flow).

The solution to this issue requires, first of all, the construction of the static characteristics of wellhead well parameters in various modes of its operation and a comparative analysis of these characteristics.

Figure 2 (a, b) shows the static characteristics of fountain and gas lift wells obtained by experimental research in field conditions in the Oil and Gas Production Department (NGDU).

It is obvious that in all cases of operation of fountain and gas lift wells, it is necessary to work with a smaller gas factor and thus economically consume gas, which is the main energy resource. To ensure the maximum selection of oil from the wells, taking into account the minimization of the total gas flow rate, it is necessary to control the operation of the wells in a certain operating range at which the required volume of oil production can be fulfilled and the technological properties of the well can not be violated.

To determine the operating range, it is necessary to take into account some technological limitations on the minimum and maximum oil withdrawals from each well. Based on our field observations and research experiments, as well as previous work, this operating range is selected as the area between the optimal and maximum fluid withdrawal without excessive gas consumption. Therefore, the minimum oil withdrawal is chosen so that its value corresponds to the minimum actual gas factor. The value of the maximum limit selection is determined empirically and therefore is further considered given (see Fig.3, 4)

Но при этом каждому приращению дебита нефти ΔQ_i, соответствует резкое увеличение приращения расхода газа ΔG.It should be noted that among the families of static characteristics of fountain and gas lift wells, the dependences of gas flow and oil production rate G _{n, i} = f _{3, i} (Q _i ) (oil production rate from gas consumption Q _{n, i} = f _{4, i are} very important (G _i )) (for example, Fig. 3), which are directly the main indicator of well operation, and respectively obtained from the functions G _i = f _{2, i} (d _i ), Q _i = f _{1, i} (d _i ). With each inconsistent increment in the diameter of the nozzle Δd _i , the flow rate increases (with each successive increment of the gas flow ΔG _{i the} oil flow rate increases) and, accordingly, the gas flow rate (in the range of

But at the same time, each increment in the oil flow rate ΔQ _i corresponds to a sharp increase in the increment in gas flow rate ΔG.

If we compare the values of three consecutive points, Q _i , Q _i + ΔQ _i , Q _i + 2ΔQ _{i of the} function G _i = f _{3, i} (Q _i ), after each successive increment, it is easy to make sure that the current value of the function G _i = f _{3, i} (Q _i ) is greater than its previous value, i.e. f _{3, i} (Q _i + ΔQ)> f _{3, i} (Q _i ) and in addition, f _{3, i} (Q _i + 2ΔQ) - f _{3, i} (Q _i + ΔQ)> f _{3, i} ( Q _i + ΔQ) - f _{s, i} (Q _i ). This makes it possible to talk about the monotonicity and convexity of the function G _i = f _{3, i} (Q _i ) (Q _i = f _{4, i} (G _i )) in the range of

First of all, we note some important mathematical properties of these dependencies.

, (Q_imin≤Q_i≤Q_imax; С_imin≤G_i≤G_imax) можно описать квадра-тичными и линейными уравнениями.Firstly, the curves of the dependence of the oil flow rate, the gas flow rate on the nozzle diameter Q _i = f _{1, i} (d _i ), G _i = f _{2, i} (d _i ), as well as the curves of the gas flow rate from the oil flow rate G _i = _{3 f, i (Q i) [Q} i = f _{4, i} (G _i)] in the range of change d _imin ≤d _i ≤d _imax,

_{, (Q imin ≤Q i ≤Q imax} ; C _imin ≤G _i ≤G _imax) can be described cal and quadra-linear equations.

являются монотонными функциями. Кроме того, квадратичные и линейные функцииSecondly, all the functions Q _i = f _{1, i} (d _i ), G _i = f _{2, i} (d _i ) and G _i = f _{3, i} (Q _i ) [Q _i = f _{4, i} ( G _i )] in the range of variation of d _imn ≤d _i ≤d _imax ,

are monotonous functions. In addition, quadratic and linear functions

(Q_imin≤Q_i≤Q_imax; G_imin≤G_i≤G_imax) являются выпуклыми функциями.changes in the range d _imin ≤d _i ≤d _imax,

_{(Q imin ≤Q i ≤Q imax;} G imin ≤G i ≤G imax) are convex functions.

As you know, a function f (x) is called convex or, more precisely, convex down (up) if it is defined on a convex set M and for any two points x ₁ and x _{2 of} this set the values of f (x) of the function at any point x the segment [x ₁ , x ₂ ] does not exceed the value at the same point defined on this segment with the values f (x ₁ ) and f (x ₂ ) at its end points. Wherein:

(фиг.2а),- all the curves of the dependence of oil production on the diameter of the fitting of the wells Q _i = f _{1, i} (d _i ) are convex upwards, since the coefficients

(figa),

(фиг.2в),- all the curves of gas flow versus the diameter of the nozzle of the wells G _i = f _{2, i} (d _i ) are convex downward, since the coefficients;

(figv),

(фиг.4),- all the curves of gas consumption versus oil flow rate G _i = f _{3, i} (Q _i ) are convex down, since the coefficients

(figure 4)

(фиг.3).- all the curves of oil flow rate versus gas flow rate Q _i = f _{3, i} (G _i ) are convex upwards, since the coefficients

(figure 3).

Thus, after identifying the static characteristics of the operating parameters, we obtained mathematical models of wells in the form of square and linear equations. For structural parametric identification of well characteristics, the least squares methods are used [for the family of characteristics Q _i = f _{1, i} (d _i ), G _i = f _{2, i} (d _i )] and uniform approximation [for the family of characteristics Q _i = f _{3 , i} (G _i ), G _i = f _{4, i} (Q _i )].

It should be noted that over time, the technological parameters of the reservoir - drainage zone - face - lifting elevator system change. Typically, such changes in well parameters occur within 1 ÷ 1.5 months. Naturally, this leads to the need to refine the mathematical model of the object. Moreover, verification of its adequacy and finding new coefficients of polynomials are required.

For local optimization of operating modes of fountain wells, it is necessary to regulate the gas factor. To do this, we must strive to ensure that each fountain well operates in a mode with minimal gas extraction, which would contribute to the optimal use of the reservoir energy resource (work with a minimum gas factor). For local optimization of a gas-lift (continuous) well, as noted earlier, it is possible to operate according to several optimality criteria (subject to the specified restrictions on the selection of fluid from the wells) imposed by the field development project. These criteria are:

- maximum total oil production for given resources of the working agent;

- maximum current profit under the same conditions or with unlimited resource of the working agent;

- the minimum consumption of the working agent for a given selection of oil.

When optimizing the operation of a system of gas lift wells, they usually proceed from the already set pressure of the compressed gas, which is determined during the design of the field development.

When establishing local optimization of operating modes, we will focus on the criteria - the minimum consumption of the working agent for a given oil selection (a possible option is the maximum selection at the required consumption of the working agent).

The solution to the general problem of monitoring and controlling the operating modes of wells based on microprocessor technology (ARAZ terminal) can be carried out as follows:

- control (measurement, data collection and output, linear and non-linear transformations of process variables, alarm, indication, data recording);

- control (dynamic optimization of the object, the establishment and maintenance of specified modes and complete invariance to various disturbing influences);

- logical control (the implementation of combinational circuits when locking, starting and stopping equipment and apparatus for wells, the implementation of finite state machines in controlling cyclic processes);

- analysis of object dynamics (identification of an object model in the form of difference or differential equations by static or analytical methods when conducting an active and passive experiment on an object);

- static optimization (redistribution of optimal oil withdrawals for wells in the field, taking into account the plan for oil production);

- solving the problem of operational accounting and reporting of petroleum products, analysis tasks, diagnostic tasks, forecasting tasks, etc.

Algorithms for the functioning of the control system and optimal control of well operation modes based on the ARAZ control terminal in real time include: measuring technological parameters of wells, their transformation and processing; building static and dynamic well models; experimental studies of technological parameters of wells; checking the adequacy of models; algorithms for the optimal distribution of oil withdrawals between wells, algorithms for accounting and forecasting technological parameters of wells.

) установить скважинам такой режим их работы, чтобы суммарный дебит нефти этих конкретных скважин удовлетворял требуемому заданию по добыче нефти (группы скважин кустов) промысла, но при этом сумму фактического расхода газа (расхода рабочего газа) отдельных скважин необходимо приводить к минимуму с обеспечением безотказной работы скважин, не допуская при этом технологических нарушений в них.Thus, we turn to solving the problem of the optimal distribution of oil production rates between wells. We formulate the problem of optimal control of the operation mode of the groups of fountain and gas lift wells as follows: by adjusting the diameters of the nozzles d _i (

) set the wells to such a mode of operation that the total oil production rate of these specific wells meets the required task for oil production (group of well wells) of the field, but the amount of actual gas flow (working gas flow) of individual wells must be minimized to ensure trouble-free operation wells, while avoiding technological violations in them.

минимизирующих функционалFormulation of the problem. It is required to find the values of the diameters of the nozzles d _i ,

minimizing functionality

and satisfying conditions

Here Z is the sum of gas consumption for all wells; I is the total oil production rate of the well;

- расход газа i-ой скважины,

- gas flow rate of the i-th well,

- дебит нефти i-ой скважины,

- oil flow rate of the i-th well,

- количество скважин с нелинейными характеристиками,

- количество скважин с линейными характеристиками). Коэффициенты:

- скважины с линейными характеристиками);

и т.д. Необходимо отметить, что при выборе значений d_{i max} и d_i,kp учитываются величины обводненности и соответственно минимального буферного давления, ниже которого нельзя эксплуатировать скважину.N is the number of wells (

- the number of wells with non-linear characteristics,

- the number of wells with linear characteristics). Odds:

- wells with linear characteristics);

etc. It should be noted that when choosing the values of d _{i max} and d _{i, kp, the} values of water cut and, accordingly, the minimum buffer pressure, below which the well cannot be operated _, are taken into account.

If

then d _i0 is a solution to problem (1.1) ... (1.3).

If

it is necessary to solve the problem

и выразив через q_i диаметр d_i=f(q_i) и расход газаDenoting the oil flow rate through q _i ,

and expressing through q _{i the} diameter d _i = f (q _i ) and the gas flow

(см. фиг.4), приведем задачи (1.4)÷(1.6)к виду

(see figure 4), we bring the problem (1.4) ÷ (1.6) to the form

аппроксимируется выражением вида

где

Dependence

approximated by an expression of the form

Where

Problem (1.7) ... (1.9) belongs to the class of mathematical programming problems with quadratic criteria and constraints. Considering that in the corresponding problem (1.7) ... (1.9) the function (1.7) in the ranges of variation (1.9) is monotonic and convex in q _i , we determine the effectiveness of the proposed algorithm for solving (1.4) ... (1.6) based on the general ideas of convex programming.

The structure of the algorithm for solving the problem is as follows (figure 1):

и выбирается оптимальный шаг по ΔQ (где ΔQ=const).1. The starting point of movement is selected, which is Q _{n, i} (d _{i min} ), G _{n, i} (d _{i min} ),

and the optimal step in ΔQ is chosen (where ΔQ = const).

2. The unit increment of each variable Q _{n, i} (d _{i min} ) = Q _i , Q _{i =} Q _{n, i} + ΔQ is given and calculated from d _i = f (Q _i ) is the value of d _i for all wells.

)=d_max(Q_i), данная скважина исключается из дальнейшего рассмотрения и запоминается

3. The condition d _i <d _{i max is} checked, if yes, then go to the next paragraph (item 4), if d _i > d _{i max} , then ΔQ '= Q _i (d _{i max} ) -Q _i (d _i ) and it is provided d _m (Q _i + ΔQ ′) = d _m (

) = d _max (Q _i ), this well is excluded from further consideration and stored

4. Next, the value of the objective function g _i for all wells d _i = f (G _i ) is calculated from d _i and the increment ΔG _i = G _i -G _{n, i is} determined.

5. The minimum value ΔG _{k is} selected from all ΔG and a new d _k corresponding to the well (where ΔG _k -minimum) is set, and for the remaining d _i = d _{n, i} , i ≠ k.

(соответственно d_k), для остальных скважин Q_н,i; вычисляются текущие значения и проверяется

Если да, то задача решена, если нет, то необходимо вернуться в пункт 2.6. The new value is remembered.

(respectively d _k ), for the remaining wells Q _{n, i} ; current values are calculated and checked

If yes, then the problem is solved, if not, then it is necessary to return to paragraph 2.

Now we define the step ΔQ (machine value) that provides the given accuracy of finding the solution according to the proposed algorithm, so that in the next steps of the increments in ΔQ the following conditions are satisfied:

In this case, the given well is excluded from further consideration and the values of its parameters are stored at the last increment step Q _m and G _m , where d _m (Q _m ) = d _max , d _m (G _m ) = d _max , under which condition (1.10 )

(при линейном случае зависимости

).We find the step ΔQ, where condition (1.10) is satisfied. To this end we choose the wellbore, wherein the average oil flow rate in the range of change d _{i min} ≤d _i ≤d _{i max} is minimum among all wells. Next, we use the formula Q _i = f _i (d _i ), in which

(in the linear case of dependence

)

Даем приращение диаметра штуцера d_i0+Δd_i=d_i. Значение приращений по диаметру штуцера выбираем Δd_i=0,1 мм, так как значение, меньше 0,1 мм, в промысловых условиях не имеет физического смысла. Тогда с учетом приращений по Δd_i находим увеличение функции Q_i=f_i(d_i)For the initial values of d _{i, 0, we} write the function Q _i = f (d _i ) and obtain

We give the increment of the diameter of the nozzle d _i0 + Δd _i = d _i . The value of the increments in the diameter of the fitting is chosen Δd _i = 0.1 mm, since a value less than 0.1 mm in the field does not have physical meaning. Then, taking into account increments in Δd _i we find an increase in the function Q _i = f _i (d _i )

From (1.11) we find ΔQ = Q _{i, 1} -Q _{i, 0} , where ΔQ is the optimal increment.

Now, if d _k (Q _i + ΔQ) <d _{i max} , then the transition to the next step continues. Denoting Q _i + ΔQ = Q _k , for the next step we write d ' _k (Q _k + ΔQ). If d ' _k (Q _k + ΔQ)> d _{i max} , then the transition to the next step stops and it is necessary in the last step to satisfy the equality d _m (Q _k + ΔQ') = d _{i max} for this well. This means that instead of ΔQ it is necessary to find a value of ΔQ 'so that it satisfies in the last step an increment of the condition d _m (Q _k + ΔQ') = d _{i max} .

Find ΔQ ', ΔQ' = Q _i (d _{i max} ) -d _k (Q _k ) = Q _i (d _{i max} ) -d _k (Q _i + ΔQ). Here d _k (Q _i + ΔQ) <d _{i max} . According to the found ΔQ ', d _m (Q _k + ΔQ') = d _{i max} (Q _i ) is provided, where d _m = d _{i max} .

Thus, the proposed algorithm allows us to solve the problem of optimal redistribution of oil production rate and gas flow rate for fountain and gas-lift wells.

Claims (1)

A method for distributing oil production between fountain and gas lift wells, including measuring the technological parameters of the wells - gas flow rate, oil production rate, buffer pressure, water cut, their conversion and processing, building static models of the well, experimental studies of the technological parameters of the wells, checking the adequacy of the models, developing distribution algorithms the selection of oil between wells, while adjusting the diameters of the nozzles set the wells to such a mode of operation that the amount the oil flow rate of specific fountain and gas lift groups of wells or field clusters satis fi ed the required oil production task, but the sum of the actual gas flow for fountain wells and working gas for individual gas lift wells is minimized to ensure trouble-free operation of these wells, avoiding technological violations in them.

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