The Detectable Radius of an Oil Well Considering Pressure Gauge Resolution Ratio

2012 ◽  
Vol 560-561 ◽  
pp. 1188-1194
Author(s):  
Jun Tai Shi ◽  
Xiang Fang Li ◽  
Lei Zhang ◽  
Wei Na Ren ◽  
Le Zhong Li ◽  
...  

For a case of constant-rate liquid production from a single well centered in a horizontal, homogeneous-acting, isopachous, and infinite reservoir, based on fundamentals of fluid flow in porous media the bottom hole flowing pressure never stabilize. In the process of field well testing, however, pressure values measured by the pressure gauge which has a definite resolution value will not change after a period, so the bottom hole flowing pressure can be considered to be stabilized. According to this situation, through theoretical derivation, a stabilized time formula is firstly proposed, by which the time after which the bottom hole flowing pressure measured with a pressure gauge will be stabilized can be calculated, and the stabilized time for a given pressure gauge is in direct proportion to the liquid producing rate, but in inverse proportion to the resolution ratio of the pressure gauge. Applied the stabilized time formula, a new formula of detectable radius can be derived, by which the effect of resolution of the pressure gauge can be considered. Secondly, the time after which the value of the pressure gauge measured in the bottom hole of the observation well starts to change during interference testing is obtained, and the time is related to the fluid flow rate and the distance between the producing well and the observation well. The conclusion can be applied as a reference in the design process of working system during well testing.

2020 ◽  
Vol 21 (6) ◽  
pp. 337-347
Author(s):  
A. H. Rzayev ◽  
G. A. Guluyev ◽  
F. H. Pashayev ◽  
As. H. Rzayev ◽  
R. Sh. Asadova

This paper presents a proposed new indirect method determining instantly oil well debit using developed mathematical models. As a result integrated analysis using the models it has been revealed correlation between oil well debit and well throw out flow temperature. Therefore putting purpose was obtained. Mathematical models are developed for the distribution of fluid flow temperature along the length of the tubing from the well bottom to the wellhead and along the length of the oil pipeline from the collector of oil wells to the oil treatment unit. On the basis of experimental data, the authors propose formulas in the form of the relationship between oil emulsion (OE) viscosity, the flow temperature and concentration of water globule in OE and the coefficient of heat transfer from the fluid flow in the wellbore (WB) to the rock, and heat capacity and thermal conductivity of gas, water, rock and steel of the WB walls. This effect is demonstrated in the constructed diagrams. It is shown bottom temperature jump as a result of the Joule Thomson drosseling effect then connective transmitted up at flow rate v. In such case well-head or well outlet oil mixture (OM) flow temperature depend more of volume of stream flow than of bottom hole temperature. Thought in the paper, do not taking into consideration great casing annulus areas influence to the well outlet flow temperature. As shown from supporting paper the relative values og the thermal conductivity of the liquid column and gas column present in the casing annulus order less than well bore (WB) wall thermal conductivity. Consequently well outlet OM flow temperature will depends not only of the volume of stream flow, also of the bottom hole temperature and of the gas column and liquid column.A new method for determining the oil well flow rate by measuring the downstream temperature is developed. A mathematical model is proposed that allows calculating the thermal profile of the fluid along the wellbore for determining the oil well flow rate with account of the geothermal gradient in the rock surrounding the wellbore. It is shown, that unlike the existing methods the new proposed method allows determining the instantaneous discharge of a well very easily. One of the actual challenges in fluid (oil, water and gas) transportation from wells to oil treatment installation is determination of a law of temperature distribution along the length of a pipeline at low ambient temperature. That temperature leads to increase in viscosity and deposition of wax on inner surface of a pipe. To overcome that challenge it is needed to consider several defining characteristics of formation fluid (FF) flow. Complexity of a solution is caused by two factors. From the one hand, in most cases (especially on a late stage of field development) FF is an oil emulsion (OE) that contains gas bubbles. From the other hand, temperature gradient between fluid flow and the environment has significant value (especially in the winter period of the year). At the same time, the higher content of emulsified water droplets (EWD) in OE and lower flow temperature, the higher FF viscosity, and consequently productivity (efficiency) of oil pumping system is reduced. Performed research and analysis of field experimental data showed that a function of oil viscosity versus temperature has a hyperbolic law; a function of OE viscosity versus concentration of EWD has a parabolic one. A heat balance for a certain section of a pipeline in steady state of fluid motion using a method of separation of variables was established taking into account above mentioned factors, Fourier’s empirical laws on heat conductivity and Newton’s law on heat transfer. As a result, unlike existing works, an exponential law of distribution of temperature along the length of a pipeline is obtained. A law takes into account nonlinear nature of change in viscosity of OE from change in temperature of flow and concentration of water in an emulsion. As a result, in contrast to the existing works, the proposed exponential law of temperature distribution along the length of the pipeline is obtained, taking into account the nonlinear nature of variation of OE viscosity with the change in the flow temperature and the concentration of water in the emulsion. The results of the calculation are presented in the form of a table and graphs.


Geofluids ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Ruichao Zhang ◽  
Yuqiong Yin ◽  
Liangfei Xiao ◽  
Dechun Chen

Based on the informatization and intelligent construction of an oilfield, this paper proposes a new method for calculating inflow performance relationship in sucker rod pump wells, which solves the limitations of current IPR curve calculation method in practical application. By analyzing the forming principle of the dynamometer card, the plate of abnormal dynamometer card is created innovatively, and the recognition model of abnormal dynamometer card based on “feature recognition” is established to ensure the accuracy of the dynamometer card. By analyzing the curvature of each point on the curve of downhole pump dynamometer card, the opening and closing points of standing valve and traveling valve are determined, and the models for calculating fluid production and bottom hole flowing pressure are established to obtain the data of fluid production and bottom hole flowing pressure of sucker rod pump wells. Finally, a calculation model of inflow performance relationship fitted with the calculated fluid production and bottom hole flowing pressure data based on genetic algorithm is established to realize calculation of oil well inflow performance relationship curve. The field application and analysis results show that the inflow performance relationship curve calculated by the model in this paper fits well with the measured data points, indicating that the calculation model has high accuracy and can provide theoretical and technical support for the field. Moreover, the real-time acquisition of dynamometer cards can provide real-time data source for this method, improve the timeliness of oil well production analysis, and help to reduce the production management costs and improve the production efficiency and benefit.


Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4541 ◽  
Author(s):  
Xin Feng ◽  
Qiang Feng ◽  
Shaohui Li ◽  
Xingwei Hou ◽  
Mengqiu Zhang ◽  
...  

The low-distortion processing of well-testing geological parameters is a key way to provide decision-making support for oil and gas field development. However, the classical processing methods face many problems, such as the stochastic nature of the data, the randomness of initial parameters, poor denoising ability, and the lack of data compression and prediction mechanisms. These problems result in poor real-time predictability of oil operation status and difficulty in offline interpreting the played back data. Given these, we propose a wavelet-based Kalman smoothing method for processing uncertain oil well-testing data. First, we use correlation and reconstruction errors as analysis indicators and determine the optimal combination of decomposition scale and vanishing moments suitable for wavelet analysis of oil data. Second, we build a ground pressure measuring platform and use the pressure gauge equipped with the optimal combination parameters to complete the downhole online wavelet decomposition, filtering, Kalman prediction, and data storage. After the storage data are played back, the optimal Kalman parameters obtained by particle swarm optimization are used to complete the data smoothing for each sample. The experiments compare the signal-to-noise ratio and the root mean square error before and after using different classical processing models. In addition, robustness analysis is added. The proposed method, on the one hand, has the features of decorrelation and compressing data, which provide technical support for real-time uploading of downhole data; on the other hand, it can perform minimal variance unbiased estimates of the data, filter out the interference and noise, reduce the reconstruction error, and make the data have a high resolution and strong robustness.


2010 ◽  
Vol 13 (11) ◽  
pp. 1033-1037
Author(s):  
Muhammad R. Mohyuddin ◽  
S. Islam ◽  
A. Hussain ◽  
A. M. Siddiqui

2019 ◽  
Vol 55 (11) ◽  
pp. 9592-9603
Author(s):  
Chul Moon ◽  
Scott A. Mitchell ◽  
Jason E. Heath ◽  
Matthew Andrew

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