Increasing Oil Production by Gas Lift Injection Point Detection Based on Well Test Data: Field Experience in the Handil Field

2020 ◽  
Author(s):  
A. M. Andari
Keyword(s):  
Computational Simulation ◽  
Oil Production ◽  
Pressure Profile ◽  
Well Testing ◽  
Well Test ◽  
Success Rates ◽  
Injection Point ◽  
East Kalimantan ◽  
Casing Pressure ◽  
Gas Lift

The Handil field is one of the mature fields in the Mahakam Delta, East Kalimantan, Indonesia. This field is widely known as an oil producer for more than 40 years with peak production of 180,000 BOPD in 1977 and has been challenging in terms of oil production decline ever since. Today, this field delivers ~16,000 BOPD from 115 active wells with more than 90% of oil production coming from gas lifted wells. Therefore, evaluating gas lift performance is very crucial to maintain hydrocarbon production of the field. As a gas lift well is produced, it is common to find gas lift unloader damage, sealing element problems, or even leaks at the tubing due to aging of equipment that degrades the gas lift performance. This paper explains the use of well testing data on investigating the performance of gas lift by estimating gas lift injection depth. The best fit vertical lift correlation should be chosen to represent actual pressure profile of the wells inside the tubing and annulus casing pressure. Estimated injection point is derived from gas lift unloader valve opening status or meeting point between tubing and casing pressure profile. The calculation was done using computational simulation and was applied for every flowing gas lifted well in an integrated module. Based on the simulation, wells that were found to encounter behavior anomalies requested to perform P-T (pressure temperature) + spinner surveys to confirm leak points prior to leak isolations. Based on 3 proven leak cases, it is confirmed that estimated gas lift injection point from simulation versus production logging survey are in line. In 2019, we had 6 gas lift well cases that were confirmed to have a leak and continued with a leak isolation program. After these wells were put back into production, it gave cumulative oil production of up to almost 100,000 Bbls oil. The high success rates of this method verifies the applicability of this effective approach to maintain gas lift performance and is easy to replicate for others PSC companies.

Model Reformulation and Global Optimization of Oil Production Using Gas Lift

2016 ◽  
Vol 55 (38) ◽  
pp. 10114-10120 ◽  
Author(s):  
Mariana Carvalho ◽  
Argimiro R. Secchi ◽  
Miguel Bagajewicz
Keyword(s):  
Global Optimization ◽  
Oil Production ◽  
Model Reformulation ◽  
Gas Lift

Production Optimization using Multiphase Well Testing: A Case Study from East Kalimantan, Indonesia

2001 ◽  
Author(s):  
Albertus Retnanto ◽  
Ben Weimer ◽  
I Nyoman Hari Kontha ◽  
Heru Triongko ◽  
Azriz Azim ◽  
...  
Keyword(s):  
Production Optimization ◽  
Well Testing ◽  
East Kalimantan

A Back Allocation Methodology to Estimate the Real-Time Flow and Assist Production Monitoring

2021 ◽  
Author(s):  
Gabriela Chaves ◽  
Danielle Monteiro ◽  
Virgilio José Martins Ferreira
Keyword(s):  
Real Time ◽  
Input Data ◽  
Oil Field ◽  
Well Testing ◽  
Well Test ◽  
Time Data ◽  
Time Flow ◽  
Well Model ◽  
Operational Information ◽  
The Individual

Abstract Commingle production nodes are standard practice in the industry to combine multiple segments into one. This practice is adopted at the subsurface or surface to reduce costs, elements (e.g. pipes), and space. However, it leads to one problem: determine the rates of the single elements. This problem is recurrently solved in the platform scenario using the back allocation approach, where the total platform flowrate is used to obtain the individual wells’ flowrates. The wells’ flowrates are crucial to monitor, manage and make operational decisions in order to optimize field production. This work combined outflow (well and flowline) simulation, reservoir inflow, algorithms, and an optimization problem to calculate the wells’ flowrates and give a status about the current well state. Wells stated as unsuited indicates either the input data, the well model, or the well is behaving not as expected. The well status is valuable operational information that can be interpreted, for instance, to indicate the need for a new well testing, or as reliability rate for simulations run. The well flowrates are calculated considering three scenarios the probable, minimum and maximum. Real-time data is used as input data and production well test is used to tune and update well model and parameters routinely. The methodology was applied using a representative offshore oil field with 14 producing wells for two-years production time. The back allocation methodology showed robustness in all cases, labeling the wells properly, calculating the flowrates, and honoring the platform flowrate.

Unlocking Idle Production in an Offshore Sandstone Oil Field With Gas Hydrate Issues

2021 ◽  
Author(s):  
Babalola Daramola
Keyword(s):  
Gas Hydrate ◽  
Oil Production ◽  
Oil Field ◽  
Third Party ◽  
Flow Assurance ◽  
Well Testing ◽  
Production Wells ◽  
Oil Flow ◽  
Offshore Oil ◽  
Production Losses

Abstract This publication presents how an oil asset unlocked idle production after numerous production upsets and a gas hydrate blockage. It also uses economics to justify facilities enhancement projects for flow assurance. Field F is an offshore oil field with eight subsea wells tied back to a third party FPSO vessel. Field F was shut down for turnaround maintenance in 2015. After the field was brought back online, one of the production wells (F5) failed to flow. An evaluation of the reservoir, well, and facilities data suggested that there was a gas hydrate blockage in the subsea pipeline between the well head and the FPSO vessel. A subsea intervention vessel was then hired to execute a pipeline clean-out operation, which removed the gas hydrate, and restored F5 well oil production. To minimise oil production losses due to flow assurance issues, the asset team evaluated the viability of installing a test pipeline and a second methanol umbilical as facilities enhancement projects. The pipeline clean-out operation delivered 5400 barrels of oil per day production to the asset. The feasibility study suggested that installing a second methanol umbilical and a test pipeline are economically attractive. It is recommended that the new methanol umbilical is installed to guarantee oil flow from F5 and future infill production wells. The test pipeline can be used to clean up new wells, to induce low pressure wells, and for well testing, well sampling, water salinity evaluation, tracer evaluation, and production optimisation. This paper presents production upset diagnosis and remediation steps actioned in a producing oil field, and aids the justification of methanol umbilical capacity upgrade and test pipeline installations as facilities enhancement projects. It also indicates that gas hydrate blockage can be prevented by providing adequate methanol umbilical capacity for timely dosing of oil production wells.

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 Field Test and Analytical Study of Intermittent Gas Lift

1974 ◽  
Vol 14 (05) ◽  
pp. 502-512 ◽  
Author(s):  
A.B. Neely ◽  
J.W. Montgomery ◽  
J.V. Vogel
Keyword(s):  
Montgomery County ◽  
Pressure Gradients ◽  
Time Decay ◽  
Controlled Experiments ◽  
Gas Velocity ◽  
Liquid Slug ◽  
Valve Stem ◽  
Casing Pressure ◽  
Solid Liquid ◽  
Gas Lift

Abstract A series of controlled experiments of intermittent gas life were carried out in an instrumented well in the Conroe field, Montgomery County, Tex. The well was equipped with seven pressure transducers over the length of the tubing string so that progress of the lifted slug of liquid could be followed up the tubing. Unique to the experimental setup was a surface-controlled, bottom-hole hydraulic valve that allowed for letting a liquid load into the tubing, closing the valve, and isolating the well from the controlled test. Thus, individual intermittent slugs could be studied independent of the well performance. A wide range of slug sizes and injection gas volumes was covered in the 52 test runs.Understanding the action of the gas-life valve is quite important in predicting intermittent-gas-lift performance. Gas-Lift valve action depends somewhat performance. Gas-Lift valve action depends somewhat on the pressure and forces acting upon the stem of the valve. Gas-life literature has assumed that this pressure is equal to the pressure in the casing once pressure is equal to the pressure in the casing once the valve opens. Tests carried out as a result of valve action seen in the instrumented well clearly indicate that this assumption is not valid. Some pressure between the casing pressure and the tubing pressure between the casing pressure and the tubing pressure will exist on the valve stem when the valve pressure will exist on the valve stem when the valve is open; and it is extremely important to be aware of this in predicting valve action. Some design techniques predict the amount of solid liquid slug that will be predict the amount of solid liquid slug that will be brought to the surface and assume that any additional liquid produced in the afterflow of gas will be negligible. It was observed in these tests that a significant portion of the liquid produced at the surface sometimes as much as 50 percent was contributed by this afterflow there will be a considerable discrepancy between predicted and actual results.Liquid recovery from individual runs did not correlate directly with any of the measured parameters. However, it appears that the amount of the liquid slug that is not produced can be correlated with the average gas velocity produced can be correlated with the average gas velocity below the slug. Since the starting slug size is known, the correlation can be used as a predictive technique in intermittent-gas-lift design. The design method has been compared with a field test. Introduction Although intermittent gas lift has been used for artificial lift in oil wells for many years, little concrete technology has been developed for it. Design methods and behavior predictions are as much an art as a science. There have predictions are as much an art as a science. There have been two major attempts to remedy the situation. White et al. attempted to analyze the motion of a finite slug of liquid propelled to the surface by gas injected at high pressure underneath. Supporting their premise by a modicum pressure underneath. Supporting their premise by a modicum of experimentation, they published results in the form of design curves. Brown and Jessen, on the other hand, attempted no analytical solution, but did extensive field testing to develop an empirical foundation for intermittent-gas-lift technology. Unfortunately, there was considerable discrepancy in the results of the two studies.To improve the technology in intermittent gas lift, Shell Oil Co, ran a series of controlled experiments in a gas-life well in the Conroe Field, Montgomery County, Tex. The well instrumentation necessary to carry out the tests is shown in Figs. 1 and 2. (The instrumentation technology was provided by B. C. Sheffield of Shell Development Co.)To predict intermittent-lift behavior, analytical methods are needed to calculate the time rate behavior of the casing gas pressure and volume, the flow of gas through a gas-lift valve, the velocity with which a liquid slug will be raised to the surface by this gas, the amount of liquid that will be produced at the surface and the amount left behind, the pressure gradients during the process, and the time decay pressure gradients during the process, and the time decay curve for the blowdown of gas pressure after the slug has surfaced. None of these functions is independent of the others and all must be considered simultaneously in predicting lift behavior. SPEJ p. 502

scholarly journals Data Processing Method of Well Testing

2021 ◽  
Vol 134 (3) ◽  
pp. 35-38
Author(s):  
A. M. Svalov ◽  
Keyword(s):  
Boundary Condition ◽  
Asymptotic Expansion ◽  
Test Data ◽  
Traditional Method ◽  
Processing Method ◽  
Well Testing ◽  
Well Test ◽  
Conductivity Equation ◽  
Complete Asymptotic Expansion ◽  
Data Processing Method

Horner’s traditional method of processing well test data can be improved by a special transformation of the pressure curves, which reduces the time the converted curves reach the asymptotic regimes necessary for processing these data. In this case, to take into account the action of the «skin factor» and the effect of the wellbore, it is necessary to use a more complete asymptotic expansion of the exact solution of the conductivity equation at large values of time. At the same time, this method does not allow to completely eliminate the influence of the wellbore, since the used asymptotic expansion of the solution for small values of time is limited by the existence of a singular point, in the vicinity of which the asymptotic expansion ceases to be valid. To solve this problem, a new method of processing well test data is proposed, which allows completely eliminating the influence of the wellbore. The method is based on the introduction of a modified inflow function to the well, which includes a component of the boundary condition corresponding to the influence of the wellbore.

Pressure Analysis for Fractured Wells

1972 ◽  
Author(s):  
Alain C. Gringarten ◽  
Henry J. Ramey ◽  
R. Raghavan
Keyword(s):  
Skin Effect ◽  
Time Pressure ◽  
Physical Nature ◽  
Well Testing ◽  
Well Test ◽  
Time Data ◽  
Well Test Analysis ◽  
Test Analysis ◽  
Straight Line ◽  
Short Time

INTRODUCTION During the last few years, there has been an explosion of information in the field of well test analysis. Because of increased physical understanding of transient fluid flow, the entire pressure history of a well test can be analyzed, not just long-time data as in conventional analysis.! It is now often possible to specify the time of beginning of the correct semilog straight line and determine whether the correct straight line has been properly identified. It is also possible to identify wellbore storage effects and the nature of wellbore stimulation as to permeability improvement, or fracturing, and perform quantitative analyses of these effects. These benefits were brought about in the main by attempts to understand the short-time pressure data from well testing, data which were often classified as too complex for analysis. One recent study of short-time pressure behavior2 showed that it was important to specify the physical nature of the stimulation in consideration of stimulated well behavior. That is, statement of the van Everdingen-Hurst infinitesimal skin effect as negative was not sufficient to define short-time well behavior. For instance, acidized {but not acid fraced) and hydraulically fractured wells did not necessarily have the same behavior at early times, even though they might possess the same value of negative skin effect.

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.

The Evolution of Green Completion in BP Khazzan Field

2021 ◽  
Author(s):  
Sultan Al Harrasi ◽  
Naren Jayawickramarajah ◽  
Taimur Al Shidhani ◽  
Daniel White ◽  
Mohamed Najwani
Keyword(s):  
Carbon Emissions ◽  
Environmentally Friendly ◽  
Pilot Project ◽  
Well Testing ◽  
Well Test ◽  
Safety Standards ◽  
Central Processing ◽  
The Usa ◽  
Reduce Emissions ◽  
Reduction Of Co2

Abstract Well Testing is the single largest contributor of carbon emissions during well operations and the industry's aspiration to reduce carbon emissions inspired the bp Oman team to identify innovative ways to reduce emissions from activities in the Khazzan field. Khazzan is characterized by tight reservoirs which requires hydraulic fracturing to release gas from the rock. After fracturing, the wells are tested/cleaned-up by flowing the well fluids and flaring the produced gas and condensate to the atmosphere. The testing removes contaminants – proppant, frac fluid, hydrogen sulphide – that could damage the downstream Central Processing Facility (CPF). ‘Green Completion’ was one of the opportunities that was identified by the bp's Oman team to remove these contaminants in an environmentally friendly manner. A Green Completion is a zero flaring concept – hydrocarbons produced during well test operations are ‘cleaned’ and then routed to processing facilities for export rather than being flared. This concept has been successfully utilized in bp's onshore US operations for over a decade. The team leveraged the experience from the USA, applying this technology to suit the conditions in Oman, but it was not simple nor straight forward. In the last two years, this process has been modified and reinvented for the operations in Oman as the company seeks to strategically reduce its global carbon footprint. In first half of 2018, the bp Wells team initiated a pilot project with the objective of developing Green Completion capability in the Khazzan field. This was the start of the journey to demonstrate bp's commitment to reducing greenhouse gas (CHG) emissions in a sustainable manner. Furthermore, bp's collaborative cross-functional aptitude allowed for expanding the use of Green Completions into the Ghazeer development, which enabled zero-emission well testing of newly drilled wells even before commissioning of the new pipeline infrastructure. Through this initiative, the region has reduced emissions and generated cash by selling the recovered hydrocarbons instead of flaring into the atmosphere during well testing operations. Since Q1 2019, the total reduction of CO2 emissions exceeded 240,000 tonnes of CO2 equivalent, which equates to taking circa 52,000 vehicles off the road for one year. The implementation of this environmentally friendly operation also adhered to strict safety standards. The rigid bp safety process guidelines ensured that all challenges and optimization opportunities were fulfilled in a safe manner. The purpose of this paper is to detail how the team pushed the technical envelope to introduce this technology and share the journey entailing extensive cross-disciplinary cooperation amongst operations, subsurface and wells teams to fulfill the zero emissions objective.

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