A Case Study on Field F Multiphase Flow Meter: How is it Better than a Conventional Test Separator?

2021 ◽  
Author(s):  
Claire Chang Li Si ◽  
Fedawin Johing ◽  
Yoon Chiang Wong ◽  
Nur Melatee Binti Mohd Fauzi ◽  
Ahmad Muzakkir Bin Mohamad ◽  
...  
Keyword(s):  
Multiphase Flow ◽  
Dynamic Models ◽  
Model Matching ◽  
Well Test ◽  
Production Rates ◽  
Reservoir Properties ◽  
Daily Production ◽  
Significant Drop ◽  
Remote Monitoring System ◽  
Well Tests

Abstract Multiphase flow meters (MPFM) have been known save costs for new installations, are compact and as effective as a test separator. Field "F" is a green field with 2 wells and has been producing since 2018 from the same reservoir. The test facilities consist of an MPFM, and F flows to a hub called Field "G". Towards Q2 of 2019, there was a significant increase in production rates from both wells without any changes to surface choke size and without enhancement jobs performed. Added to that, reservoir pressure showed steady depletion. Daily production allocation for F showed lower than usual reconciliation factor when combined with G hub production. This suboptimal allocation raised doubts about the MPFM well test readings which launched a full investigation into the accuracy of the meter. From the offshore remote monitoring system, the first suspect was the increased inlet pressure causing parameters to be out of the MPFM operating envelope range. However, after further checking, there were other pressing issues such as faulty transmitter, and low range sensors. As these issues were being dealt with amidst the COVID-19 pandemic, the process to fix the meter was longer than usual. Rectification involved troubleshooting the MPFM post performing Multi Rate Tests, back allocation check to hub production and PROSPER/GAP model matching to check on the credibility of the well tests. These efforts were made due to budget cuts, as there was no advantage to bring onboard an entire well test package (separator) to test the F wells. Post several rectifications, the liquid, gas and oil rates were within 10% difference from allocation meter back allocation and PROSPER model calculation. Reconciliation factor for field G has also increased to normal range of 0.92 to 0.95. However, the rectification also showed a significant drop in metered rates, proving that the MPFM was indeed generating incorrect well tests since Q2 2019. The drop was higher than 30% in gross production rates which lead to a better understanding of the reservoir, and corrections to be made to dynamic models for any future development projects. This hence proves that even with the similar reservoir properties in both wells, the MPFM well tests still require vigorous checking and should not be treated in the same way as a test separator. This paper will describe the efforts by surface and subsurface faculties to ensure the quality of well tests from the MPFM. For future projects considering the MPFM installation, best to frequently quality check the MPFM well test figures with a test separator. However, if that option is not feasible, the efforts in this paper can act as a guide for the field.

A Novel Well Test Data Analyzer and Process Optimizer Using Artificial Intelligence and Machine Learning Techniques

2021 ◽  
Author(s):  
Nagaraju Reddicharla ◽  
Subba Ramarao Rachapudi ◽  
Indra Utama ◽  
Furqan Ahmed Khan ◽  
Prabhker Reddy Vanam ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Real Time ◽  
Test Data ◽  
Oil Field ◽  
Well Testing ◽  
Well Test ◽  
Time Data ◽  
Real Time Data ◽  
Well Tests

Abstract Well testing is one of the vital process as part of reservoir performance monitoring. As field matures with increase in number of well stock, testing becomes tedious job in terms of resources (MPFM and test separators) and this affect the production quota delivery. In addition, the test data validation and approval follow a business process that needs up to 10 days before to accept or reject the well tests. The volume of well tests conducted were almost 10,000 and out of them around 10 To 15 % of tests were rejected statistically per year. The objective of the paper is to develop a methodology to reduce well test rejections and timely raising the flag for operator intervention to recommence the well test. This case study was applied in a mature field, which is producing for 40 years that has good volume of historical well test data is available. This paper discusses the development of a data driven Well test data analyzer and Optimizer supported by artificial intelligence (AI) for wells being tested using MPFM in two staged approach. The motivating idea is to ingest historical, real-time data, well model performance curve and prescribe the quality of the well test data to provide flag to operator on real time. The ML prediction results helps testing operations and can reduce the test acceptance turnaround timing drastically from 10 days to hours. In Second layer, an unsupervised model with historical data is helping to identify the parameters that affecting for rejection of the well test example duration of testing, choke size, GOR etc. The outcome from the modeling will be incorporated in updating the well test procedure and testing Philosophy. This approach is being under evaluation stage in one of the asset in ADNOC Onshore. The results are expected to be reducing the well test rejection by at least 5 % that further optimize the resources required and improve the back allocation process. Furthermore, real time flagging of the test Quality will help in reduction of validation cycle from 10 days hours to improve the well testing cycle process. This methodology improves integrated reservoir management compliance of well testing requirements in asset where resources are limited. This methodology is envisioned to be integrated with full field digital oil field Implementation. This is a novel approach to apply machine learning and artificial intelligence application to well testing. It maximizes the utilization of real-time data for creating advisory system that improve test data quality monitoring and timely decision-making to reduce the well test rejection.

A Proxy Flow Modelling Workflow to Estimate Gridded Dynamic Properties and Well Production Rates by Deep Learning Algorithms

2021 ◽  
Author(s):  
Soumi Chaki ◽  
Yevgeniy Zagayevskiy ◽  
Terry Wong
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Dynamic Properties ◽  
Reservoir Management ◽  
Flow Modeling ◽  
Static Properties ◽  
Production Rates ◽  
Reservoir Properties ◽  
Well Production ◽  
Reservoir Simulator

Abstract This paper proposes a deep learning-based framework for proxy flow modeling to predict gridded dynamic petroleum reservoir properties (like pressure and saturation) and production rates for wells in a single framework. It approximates the solution of a full physics-based numerical reservoir simulator, but runs much more rapidly, allowing users to generate results for a much wider range of scenarios in a given time than could be done with a full physics simulator. The proxy can be used for reservoir management tasks like history matching, uncertainty quantification, and field development optimization. A deep-learning based methodology for accurate proxy-flow modeling is presented which combines U-Net (a variant of convolutional neural network) to predict gridded dynamic properties and deep neural network (DNN) models to forecast well production rates. First, gridded dynamic properties, such as reservoir pressure and phase saturations, are predicted from static properties like reservoir rock porosity and absolute permeability using a U-Net. Then, the static properties and the dynamic properties predicted by the U-Net are input to a DNN to predict production rates at the well perforations. The inclusion of U-net predicted pressure and saturations improves the quality of the well rate predictions. The proposed methodology is presented with the synthetic Brugge reservoir discretized into grid blocks. The U-Net input consists of three properties: dynamic gridded reservoir properties (such as pressure or fluid saturation) at the current state, static gridded porosity, and static gridded permeability. The U-Net has only one output property, the target gridded property (such as pressure or saturation) at the next time step. Training and testing datasets are generated by running 13 full physics flow simulations and dividing them in a 12:1 ratio. Nine U-Net models are calibrated to predict pressures/saturations, one for each of the nine grid layers present in the Brugge model. These outputs are then concatenated to obtain the complete pressure/saturation model for all nine layers. The constructed U-Net models match the distributions of generated pressures/saturations of the numerical reservoir simulator with a correlation coefficient value of approximately 0.99 and above 95% accuracy. The DNN models approximate well production rates accurately from U-Net predicted pressures and saturations along with static properties like transmissibility and horizontal permeability. For each well and each well perforation, the production rate is predicted with the DNN model. The use of the constructed proxy flow model generates reservoir predictions within a few minutes compared to the hours or days typically taken by a full physics flow simulator. The direct connection that is established between the gridded static and dynamic properties of the reservoir and well production rates using U-Net and DNN models has not been presented previously. Using only a small number of runs for its training, the workflow matches the numerical reservoir simulator results with reduced computational effort. This helps reservoir engineers make informed decisions more quickly, resulting in more efficient reservoir management.

Production Optimization in Mature Field Through Scenario Prediction Using a Representative Network Model: A Rapid Solution Without Well Intervention

2021 ◽  
Author(s):  
Edwin Lawrence ◽  
Marie Bjoerdal Loevereide ◽  
Sanggeetha Kalidas ◽  
Ngoc Le Le ◽  
Sarjono Tasi Antoneus ◽  
...  
Keyword(s):  
Network Model ◽  
Test Data ◽  
Production Optimization ◽  
Operating Conditions ◽  
Fine Tuning ◽  
Well Test ◽  
Production Rates ◽  
Mature Field ◽  
Gas Lift ◽  
Field Production

Abstract As part of the production optimization exercise in J field, an initiative has been taken to enhance the field production target without well intervention. J field is a mature field; the wells are mostly gas lifted, and currently it is in production decline mode. As part of this optimization exercise, a network model with multiple platforms was updated with the surface systems (separator, compressors, pumps, FPSO) and pipelines in place to understand the actual pressure drop across the system. Modelling and calibration of the well and network model was done for the entire field, and the calibrated model was used for the production optimization exercise. A representative model updated with the current operating conditions is the key for the field production and asset management. In this exercise, a multiphase flow simulator for wells and pipelines has been utilized. A total of ∼50 wells (inclusive of idle wells) has been included in the network model. Basically, the exercise started by updating the single-well model using latest well test data. During the calibration at well level, several steps were taken, such as evaluation of historical production, reservoir pressure, and well intervention. This will provide a better idea on the fine-tuning parameters. Upon completion of calibrating well models, the next level was calibration of network model at the platform level by matching against the platform operating conditions (platform production rates, separator/pipeline pressure). The last stage was performing field network model calibration to match the overall field performance. During the platform stage calibration, some parameters such as pipeline ID, horizontal flow correlation, friction factor, and holdup factor were fine-tuned to match the platform level operating conditions. Most of the wells in J field have been calibrated by meeting the success criterion, which is within +/-5% for the production rates. However, there were some challenges in matching several wells due to well test data validity especially wells located on remote platform where there is no dedicated test separator as well as the impact of gas breakthrough, which may interfere to performance of wells. These wells were decided to be retested in the following month. As for the platform level matching, five platforms were matched within +/-10% against the reported production rates. During the evaluation, it was observed there were some uncertainties in the reported water and gas rates (platform level vs. well test data). This is something that can be looked into for a better measurement in the future. By this observation, it was suggested to select Platform 1 with the most reliable test data as well as the platform rate for the optimization process and qualifying for the field trial. Nevertheless, with the representative network model, two scenarios, reducing separator pressure at platform level and gas lift optimization by an optimal gas lift rate allocation, were performed. The model predicts that a separator pressure reduction of 30 psi in Platform 1 has a potential gain of ∼300 BOPD, which is aligned with the field results. Apart from that, there was also a potential savings in gas by utilizing the predicted allocated gas lift injection rate.

An Investigation of Wellbore Storage and Skin Effect in Unsteady Liquid Flow: I. Analytical Treatment

1970 ◽  
Vol 10 (03) ◽  
pp. 279-290 ◽  
Author(s):  
Ram G. Agarwal ◽  
Rafi Al-Hussainy ◽  
H.J. Ramey
Keyword(s):  
Skin Effect ◽  
Initial Period ◽  
Outer Boundary ◽  
Well Test ◽  
Time Data ◽  
Wellbore Storage ◽  
Straight Line ◽  
Pan American ◽  
Well Tests ◽  
Short Time

Agarwal, Ram G., Pan American Petroleum Corp. Tulsa, Okla., Pan American Petroleum Corp. Tulsa, Okla., Al-Hussainy, Rafi, Junior Members AIME, Mobil Research and Development Corp., Dallas, Tex., Ramey Jr., H.J., Member AIME, Stanford U. Stanford, Calif. Abstract Due to the cost of extended pressure-drawdownor buildup well tests and the possibility of acquisitionof additional information from well tests, the moderntrend has been toward development of well-testanalysis methods pertinent for short-time data."Short-time" data may be defined as pressureinformation obtained prior to the usual straight-lineportion of a well test. For some time there has been portion of a well test. For some time there has been a general belief that the factors affecting short-timedata are too complex for meaningful interpretations. Among these factors are wellbore storage, variousskin effects such as perforations, partial penetration, fractures of various types, the effect of a finiteformation thickness, and non-Darcy flow. A numberof recent publications have dealt with short-timewell-test analysis. The purpose of this paper isto present a fundamental study of the importance ofwellbore storage with a skin effect to short-timetransient flow. Results indicate that properinterpretations of short-time well-test data can bemade under favorable circumstances. Upon starting a test, well pressures appearcontrolled by wellbore storage entirely, and datacannot be interpreted to yield formation flowcapacity or skin effect. Data can be interpreted toyield the wellbore storage constant, however. Afteran initial period, a transition from wellbore storagecontrol to the usual straight line takes place. Dataobtained during this period can be interpreted toobtain formation flow capacity and skin effect incertain cases. One important result is that thesteady-state skin effect concept is invalid at veryshort times. Another important result is that thetime required to reach the usual straight line isnormally not affected significantly by a finite skineffect. Introduction Many practical factors favor short-duration welltesting. These include loss of revenue during shut-in, costs involved in measuring drawdown or buildupdata for extended periods, and limited availabilityof bottomhole-pressure bombs where it is necessaryto survey large numbers of wells. on the other hand, reservoir engineers are well aware of the desirabilityof running long-duration tests. The result is usuallya compromise, and not necessarily a satisfactoryone. This situation is a common dilemma for thefield engineers who must specify the details of specialwell tests and annual surveys, and interpret theresults. For this reason, much effort has been givento the analysis of short-time tests. The term"short-time" is used herein to indicate eitherdrawdown or buildup tests run for a period of timeinsufficient to reach the usual straight-line portions. Drawdown data taken before the traditional straight-lineportion are ever used in analysis of oil or gas portion are ever used in analysis of oil or gas well performance. Well files often contain well-testdata that were abandoned when it was realized thatthe straight line had not been reached. This situationis particularly odd when it is realized that earlydata are used commonly in other technologies whichemploy similar, or analogous, transient test. It is the objective of this study to investigatetechniques which may be used to interpret informationobtained form well tests at times prior to the normalstraight-line period. THEORY The problem to be considered is the classic oneof flow of a slightly compressible (small pressuregradients) fluid in an ideal radial flow system. Thatis, flow is perfectly radial to a well of radius rwin an isotropic medium, and gravitational forces areneglected. We will consider that the medium isinfinite in extent, since interest is focused on timesshort enough for outer boundary effects not to befelt at the well. SPEJ p. 279

scholarly journals Exposure to exogenous estrogens in food: possible impact on human development and health

1999 ◽  
Vol 140 (6) ◽  
pp. 477-485 ◽  
Author(s):  
AM Andersson ◽  
NE Skakkebaek
Keyword(s):  
Human Development ◽  
Steroid Hormones ◽  
Scientific Data ◽  
Animal Tissues ◽  
Production Rates ◽  
Daily Production ◽  
Prepubertal Children ◽  
The Us ◽  
Residue Levels ◽  
Low Levels

There has been increasing concern about the impact of environmental compounds with hormone-like action on human development and reproductive health over the past decades. An alternative but neglected source of hormone action that may be considered in this connection is hormone residues in meat from husbandry animals treated with sex steroid hormones for growth promotion. Treatment of cattle with naturally occurring or synthetic sex hormones may enhance lean muscle growth and improve feed efficiency and is therefore a very cost effective procedure for cattle producers who have used it for decades in some Western countries, including the USA and Canada. The Joint Food and Agricultural Organisation/World Health Organisation (FAO/WHO) expert committee on food additives (JECFA) and the US Food and Drug Administration (FDA) considered, in 1988, that the residues found in meat from treated animals were safe for the consumers. We have re-evaluated the JECFA conclusions regarding the safety of estradiol residues in meat in the light of recent scientific data, with special emphasis on estradiol levels in prepubertal children. These levels are needed for estimates of the normal daily production rates of estradiol in children, who may be particularly sensitive to low levels of estradiol. In our opinion, the conclusions by JECFA concerning the safety of hormone residues in meat seem to be based on uncertain assumptions and inadequate scientific data. Our concerns can be summarized as follows. 1) The data on residue levels in meat were based on studies performed in the 1970's and 1980's using radioimmunoassay (RIA) methods available at the time. The sensitivity of the methods was generally inadequate to measure precisely the low levels found in animal tissues, and considerable variation between different RIA methods for measuring steroids exists. Therefore the reported residue levels may be subject to considerable uncertainty. 2) Only limited information on the levels of the various metabolites of the steroids was given despite the fact that metabolites also may have biological activity. 3) Reliable data on daily production rates of steroid hormones were and are still lacking in healthy prepubertal children. This lack is crucial as previous guidelines regarding acceptable levels of steroid residues in edible animal tissues have been based on very questionable estimates of production rates in children. Thus, even today the US FDA bases its guidelines on the presumably highly overestimated production rates in prepubertal children given in the JECFA 1988 report. 4) The possible biological significance of very low levels of estradiol is neglected. In conclusion, based on our current knowledge possible adverse effects on human health by consumption of meat from hormone-treated animals cannot be excluded.

Value of Well Test in the determination and characterization of Natural Fractured Reservoir Properties in Large Onshore Abu Dhabi Carbonate Field

2012 ◽  
Author(s):  
Angelo Farcasanu ◽  
Cristian Ancuta ◽  
Abdul Samad ◽  
Arun T.A. Kumar ◽  
Riadh Bejaoui ◽  
...  
Keyword(s):  
Abu Dhabi ◽  
Fractured Reservoir ◽  
Well Test ◽  
Reservoir Properties

Properties of a Natural Fracture and Its Skins From Reservoir Well Tests

SPE Journal ◽  
2013 ◽  
Vol 19 (03) ◽  
pp. 390-397 ◽  
Author(s):  
M.. Prats ◽  
R.. Raghavan
Keyword(s):  
History Matching ◽  
Flow Resistance ◽  
Short Interval ◽  
Natural Fracture ◽  
Disperse Flow ◽  
Well Test ◽  
Transient Pressure ◽  
Matrix Permeability ◽  
Wide Range ◽  
Well Tests

Summary Two well tests are described that are aimed at the in-situ determination of the flow capacity (permeability-thickness product) of a natural fracture and the flow resistance of its skins at the boundaries with the reservoir matrix. Fracture skins tend to disperse flow, thus affecting the distribution of tracers in reservoir tests and contaminants and trace elements in aquifers. We are unaware of any other analytical procedure aimed at obtaining the properties of a natural fracture and its skins from subsurface measurements. Neither well test has been implemented. The well tests are modeled after previously reported analytical expressions for the transient pressure distributions in a three-region composite reservoir in a uniform-thickness reservoir in which (1) the natural fracture is represented by a thin middle region of relatively high permeability, (2) the pressure disturbance is caused by producing from a short interval in one of the outer regions, and (3) the response is measured relatively near the fracture. The source and sensor may be on the same side or on opposite sides of the fracture, distinguishing the two tests. Visualizing special completions in a horizontal well intersecting a natural fracture normally, pressure responses are given for both tests for a wide range of fracture/matrix permeability ratios and skin flow resistances for a source 190 ft from the fracture and 10 ft from the sensor and on either side of the fracture, both at the midplane of the reservoir. A simple graphical procedure, not intended to replace history matching or regression where field data are available, illustrates how the two unknowns—permeability-thickness product of a natural fracture and the flow resistance of its skins—may be estimated from two representative values of an assumed measured pressure response.

scholarly journals Features of the underground storages construction in depleted oil and gas condensate fields

2020 ◽  
Vol 244 ◽  
pp. 418-427
Author(s):  
Ramiz Gasumov ◽  
Eldar Gasumov ◽  
Yulia Minchenko
Keyword(s):  
Oil And Gas ◽  
Individual Characteristics ◽  
Gas Condensate ◽  
Construction Technology ◽  
Reservoir Properties ◽  
Daily Production ◽  
Geological Conditions ◽  
The Us ◽  
Formation Conditions ◽  
The Individual

The paper considers the features of the underground storages (US) construction in depleted oil and gas condensate fields (DOGCFs). The requirements for the structure of the formation, corresponding to the parameters of the object for possible US creation are presented. The influence of geological, hydrogeological, mining and technical rock formation conditions on the reliability and tightness of underground storages, including underground gas storages, has been evaluated. The necessary conditions for the US design are analyzed at the example of the Ach-Su oil and gas condensate field, in the presence of a well-explored trap with acceptable parameters for the construction of an underground storage. An important aspect is the geological conditions that meet the criteria for selecting the object: the required structure, the absence of fracturing faults, high reservoir properties of the formation, a sufficient volume of the deposit for the storage. Geological conditions lay the basis for determining the individual characteristics of the US construction technology at each DOGCF. The refined results for the current gas-saturated pore volume and the rate of pressure drop in the formation are presented, which makes it possible to select improved technological indicators in the course of  operation of the created US. In order to select the optimal option for the design and construction of the US, the results of economic and geological scenarios analysis were studied concurrently with the capabilities of the technological operation of the object and transport system, which can ensure the maximum daily production of the storage.

Using Transient Inflow Performance Relationships to Model the Dynamic Interaction Between Reservoir and Wellbore During Pressure Testing

2007 ◽  
Author(s):  
Aldo Costantini ◽  
Gioia Falcone ◽  
Geoffrey F. Hewitt ◽  
Claudio Alimonti
Keyword(s):  
Multiphase Flow ◽  
Flow Rate ◽  
Dynamic Interaction ◽  
Published Data ◽  
Preliminary Evaluation ◽  
Well Test ◽  
Set Up ◽  
Inflow Performance ◽  
Transient Multiphase Flow ◽  
Bottomhole Pressure

The fundamental understanding of the dynamic interactions between multiphase flow in the reservoir and that in the wellbore remains surprisingly weak. The classical way of dealing with these interactions is via inflow performance relationships (IPR’s), where the inflow from the reservoir is related to the pressure at the bottom of the well, which is a function of the multiphase flow behaviour in the well. Steady-state IPR’s are normally adopted, but their use may be erroneous when transient multiphase flow conditions occur. Transient multiphase flow in the wellbore causes problems in well test interpretation when the well is shut-in at surface and the bottomhole pressure is measured. Pressure build-up (PBU) data recorded during a test can be dominated by transient wellbore effects (e.g. phase change, flow reversal and re-entry of the denser phase into the producing zone), making it difficult to distinguish between true reservoir features and transient wellbore artefacts. This paper introduces a method to derive the transient IPR’s at bottomhole conditions in order to link the wellbore to the reservoir during PBU. A commercial numerical simulator was used to build a simplified reservoir model (single well, radial co-ordinates, homogeneous rock properties) using published data from a gas condensate field in the North Sea. In order to exclude wellbore effects from the investigation of the transient inflow from the reservoir, the simulation of the wellbore was omitted from the model. Rather than the traditional flow rate at surface conditions, bottomhole pressure was imposed to constrain the simulation. This procedure allowed the flow rate at the sand face to be different from zero during the early times of the PBU, even if the surface flow rate is equal to zero. As a result, a transient IPR at bottomhole conditions was obtained for the given field case and for a specific set of time intervals, time steps and bottomhole pressure. In order to validate the above simulation approach, a preliminary evaluation of the required experimental set-up was carried out. The set-up would allow the investigation of the dynamic interaction between the reservoir, the near-wellbore region and the well, represented by a pressured vessel, a cylindrical porous medium and a vertical pipe, respectively.

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