Unlocking By-Passed Oil with Autonomous Inflow Control Devices Through an Integrated Approach

2021 ◽  
Author(s):  
Pawan Agrawal ◽  
Sharifa Yousif ◽  
Ahmed Shokry ◽  
Talha Saqib ◽  
Osama Keshtta ◽  
...  

Abstract In a giant offshore UAE carbonate oil field, challenges related to advanced maturity, presence of a huge gas-cap and reservoir heterogeneities have impacted production performance. More than 30% of oil producers are closed due to gas front advance and this percentage is increasing with time. The viability of future developments is highly impacted by lower completion design and ways to limit gas breakthrough. Autonomous inflow-control devices (AICD's) are seen as a viable lower completion method to mitigate gas production while allowing oil production, but their effect on pressure drawdown must be carefully accounted for, in a context of particularly high export pressure. A first AICD completion was tested in 2020, after a careful selection amongst high-GOR wells and a diagnosis of underlying gas production mechanisms. The selected pilot is an open-hole horizontal drain closed due to high GOR. Its production profile was investigated through a baseline production log. Several AICD designs were simulated using a nodal analysis model to account for the export pressure. Reservoir simulation was used to evaluate the long-term performance of short-listed scenarios. The integrated process involved all disciplines, from geology, reservoir engineering, petrophysics, to petroleum and completion engineering. In the finally selected design, only the high-permeability heel part of the horizontal drain was covered by AICDs, whereas the rest was completed with pre-perforated liner intervals, separated with swell packers. It was considered that a balance between gas isolation and pressure draw-down reduction had to be found to ensure production viability for such pilot evaluation. Subsequent to the re-completion, the well could be produced at low GOR, and a second production log confirmed the effectiveness of AICDs in isolating free gas production, while enhancing healthy oil production from the deeper part of the drain. Continuous production monitoring, and other flow profile surveys, will complete the evaluation of AICD effectiveness and its adaptability to evolving pressure and fluid distribution within the reservoir. Several lessons will be learnt from this first AICD pilot, particularly related to the criticality of fully integrated subsurface understanding, evaluation, and completion design studies. The use of AICD technology appears promising for retrofit solutions in high-GOR inactive strings, prolonging well life and increasing reserves. Regarding newly drilled wells, dedicated efforts are underway to associate this technology with enhanced reservoir evaluation methods, allowing to directly design the lower completion based on diagnosed reservoir heterogeneities. Reduced export pressure and artificial lift will feature in future field development phases, and offer the flexibility to extend the use of AICD's. The current technology evaluation phases are however crucial in the definition of such technology deployments and the confirmation of their long-term viability.

SPE Journal ◽  
2021 ◽  
pp. 1-18
Author(s):  
Yingli Xia ◽  
Tianfu Xu ◽  
Yilong Yuan ◽  
Xin Xin ◽  
Huixing Zhu

Summary Natural gas hydrate (NGH) is regarded as an important alternative future energy resource. In recent years, a few short-term production tests have been successfully conducted with both permafrost and marine sediments. However, long-term hydrate production performance and the potential geomechanical problems are not very clear. According to the available geological data at the Mallik site, a more realistic hydrate reservoir model that considers the heterogeneity of porosity, permeability, and hydrate saturation was developed and validated by reproducing the field depressurization test. The coupled multiphase and heat flow and geomechanical response induced by depressurization were fully investigated for long-term gas production from the validated hydrate reservoir model. The results indicate that long-term gas production through depressurization from a vertically heterogeneous hydrate reservoir is technically feasible, but the production efficiency is generally modest, with the low average gas production rate of 4.93 × 103 ST m3/d (ST represents the standard conditions) over a 1-year period. The hydrate dissociation region is significantly affected by the reservoir heterogeneity and reveals a heterogeneous dissociation front in the reservoir. The depressurization production results in significant increase of shear stress and vertical compaction in the hydrate reservoir. The response of shear stress indicates that the potential region of sand migration is mainly in the sand-dominant layer during gas production from the hydraulically heterogeneous hydrate reservoir (e.g., sand layers interbedded with clay layers). The maximum subsidence is approximately 78 mm and occurred at the 72nd day, whereas the final subsidence is slowly dropped to 63 mm after 1-year of depressurization production. The vertical subsidence is greatly dependent on the elastic properties and the permeability anisotropy. In particular, the maximum subsidence increased by approximately 81% when the ratio of permeability anisotropy was set at 5:1. Furthermore, the potential shear failure in the hydrate reservoir is strongly correlated to the in-situ stress state. For the normal fault stress regime, the greater the initial horizontal stress is, the less likely the hydrate reservoir is to undergo shear failure during depressurization production.


2021 ◽  
Author(s):  
Fazeel Ahmad ◽  
Zohaib Channa ◽  
Fahad Al Hosni ◽  
Salman Farhan Nofal ◽  
Ziad Talat Libdi ◽  
...  

Abstract The paper discusses the pilot project in ADNOC Offshore to assess the Autonomous Inflow Control Device (AICD) technology as an effective solution for increasing oil production over the life of the field. High rate of water and gas production in horizontal wells is one of the key problems from the commencement of operation due to the high cost of produced water and gas treatment including several other factors. Early Gas breakthrough in wells can result in shut-in to conserve reservoir energy and to meet the set GOR guidelines. The pilot well was shut-in due to high GOR resulted from the gas breakthrough. A pilot project was implemented to evaluate the ability of autonomous inflow control technology to manage gas break through early in the life of the well spanned across horizontal wellbore. And also to balance the production influx profile across the entire lateral length and to compensate for the permeability variation and therefore the productivity of each zone. Each compartment in the pilot well was equipped with AICD Screens and Swell-able Packers across horizontal open hole wellbore to evaluate oil production and defer gas breakthrough. Some AICDs were equipped with treatment valve for the compartments that needed acid simulation to enhance the effectiveness of the zone. The selection factors for installing number of production valves in the pilot well per each AICD was based on reservoir and field data. Pre-modeling of the horizontal wellbore section with AICD was performed using commercial simulation software (NETool). After the first pilot was completed, a detailed technical analysis was conducted and based on the early production results from the pilot well showed that AICD completions effectively managed gas production by delaying the gas break through and restricting gas inflow from the reservoir with significant GOR reduction ±40% compared to baseline production performance data from the open hole without AICD thus increasing oil production. The pilot well performed positively to the AICD completion allowing to produce healthy oil and meeting the guidelines. The early production results are in line with NETool simulation modelling, thereby increasing assurance in the methods employed in designing the AICD completion for the well and candidate selection. This paper discusses the successful AICD completion installation and production operation in pilot well in ADNOC Offshore to manage GOR and produced the well with healthy oil under the set guidelines. This will enable to re-activate wells shut-in due to GOR constraint to help meeting the sustainable field production target.


2021 ◽  
Author(s):  
Cunliang Chen ◽  
Xiaodong Han ◽  
Wei Zhang ◽  
Yanhui Zhang ◽  
Fengjun Zhou

Abstract The ultimate goal of oilfield development is to maximize the investment benefits. The reservoir performance prediction is directly related to oilfield investment and management. The traditional strategy based on numerical simulation has been widely used with the disadvantages of long run time and much information needed. It is necessary to form a fast and convenient method for the oil production prediction, especially for layered reservoir. A new method is proposed to predict the development indexes of multi-layer reservoirs based on the injection-production data. The new method maintains the objectivity of the data and demonstrates the superiority of the intelligent algorithm. The layered reservoir is regarded as a series of single layer reservoirs on the vertical direction. Considering the starting pressure gradient of non-Newtonian fluid flow and the variation of water content in the oil production index, the injection-production response model for single-layer reservoirs is established. Based on that, a composite model for the multi-layer reservoir is established. For model solution, particle swarm optimization is applied for optimization of the new model. A heterogeneous multi-layer model was established for validation of the new method. The results obtained from the new proposed model are in consistent with the numerical simulation results. It saves a lot of computing time with the incorporation of the artificial intelligence methods. It showed that this technique is valid and effective to predict oil performance in layered reservoir. These examples showed that the application of big data and artificial intelligence method is of great significance, which not only shortens the working time, but also obtains relatively higher accuracy. Based on the objective data of the oil field and the artificial intelligence algorithm, the prediction of oil field development data can be realized. This technique has been used in nearly 100 wells of Bohai oilfields. The results showed in this paper reveals that it is possible to estimate the production performance of the water flooding reservoirs.


2021 ◽  
Author(s):  
Mohammed Al Asimi ◽  
Nasar Al Qasabi ◽  
Duc Le ◽  
Yuchen Zhang ◽  
Di Zhu ◽  
...  

Abstract After successful implementation of data analytics for steamflood optimization at the Mukhaizna heavy oil field in Oman late 2018, Occidental expanded the project to two additional areas with a total of 626 wells in 2019, followed by full field coverage of more than 3,200 wells in 2020. In 2019, two separate low-fidelity proxy models were built to model the two pilot areas. The models were updated with more features to account for additional reservoir phenomena and a larger scope. On the proxy engine side, speed and robustness were improved, resulting in reduced CPU processing time and lower cost. Because of advancements in software programing and the pilots’ encouraging production performance, full-field coverage was accelerated so the model could support the efforts in optimizing steam injection during the 2020 OPEC+ production cut, not only to comply with allotted quotas, but also to allocate the resources optimally, especially the costly steam. Good improvements have been observed in overall steamflood performance, the models’ capabilities, and the optimization workflow. The steam/oil ratio has been reduced through the increase in oil production in both expanded study areas while keeping the total steam injection volume constant. Overall field steam utilization was improved both during the 2020 OPEC+ production cuts and during the production ramp-up stage afterward. With the continuous improvement in supporting tools and scripts, most of the steam optimization process steps were automated, from preparing, checking, and formatting input data to analyzing, validating, and visualizing the model outputs. Another result of these improvements was the development of a user-friendly web application to manage the model workflow efficiently. This web app greatly improved the process of case submittals, including data preparation and QC, running models (history matching and forecasting), as well as visualization of the entire workflow. In terms of optimization workflow, these improvements resulted in less time spent by the field optimization engineer in updating, refreshing, and generating new model recommendations. It also helped reduce the time spent by the reservoir management team (RMT) to test and validate the new ideas before field implementation. This paper will describe the improvements in the proxy model and the overall optimization process, show the observed oil production increases, and discuss the challenges faced and the lessons learned.


2021 ◽  
Author(s):  
Carlos Alejandro Terrones Brand ◽  
Miguel Alejandro Basso Mora ◽  
Rajeswary Kandasamy ◽  
Sergio Comarin ◽  
Felipe Rene Bustos Guevara ◽  
...  

Abstract Mexico has set challenging oil and gas production to meet worldwide demand. In order to deliver promised oil production outputs in this challenging environment, the operator came up with efficient partnerships with key service providers to leverage resources and technical know-how whilst encouraging knowledge transfer and drilling project cost reduction. By working with various service companies, the operator creates a competitive environment where each strives to outperform the other. One such success case is in the "S" field, a heavy oil field producing via steam injection in the South of Mexico. Utilizing a creative design and execution methodology, the "S" project team succeeded to deliver improved project performance over the course of drilling the 14 wells in the campaign. The average well operational time was successfully reduced by 10%, hence maximizing the well construction index to 122 m/day and reducing overall well costs. The main strategy to optimize performance is to re-engineer solutions for profitability such as performing a study to replace OBM by WBM, designing a new wellhead system, collaborating with the rig contractor to reduce flat time activities, redesigning cement properties for losses mitigation, improvement of ROP by merging new technologies and local practices, among others. Complementary to this, the strategy is to prioritize realistic areas of improvement by the development and utilization of a new tool called Best of the Best (BoB), a methodology breaking down all well activities in order to measure its fastest time per well and then aiming to achieve that aggressive goal. Detailed follow up in the field allows to reduce operational times by allowing the wellsite team monitor and suggest new and improved ways of doing a routine task all of which result in lower costs per foot. Utilizing this BoB approach and stringent performance monitoring while drilling (pre-actual-post) activity analysis, allowed superior performance to be achieved. The project reached a 60% improvement on well times from the first well drilled to the best performing well. The best well was drilled in 8.68 days versus a field average of 18 days (217 m/day construction index). This generated 369,000 bbls of earlier oil production, 176 days ahead vs client expectations. Furthermore, in coordination with field staff, lessons learned were captured. But this is not enough since fast and effective communication is required, and the BoB methodology provides the solution to share optimization tricks quickly and effectively between crews, to continue well to well improvement and overall project and field level learning. Improved well delivery results is possible only by aligning the detailed planning and execution follow up in both the wellsite and a remote operations centre which monitored drilling activity in real time from town. This synergy and proactive communication system is also a key factor in the project delivery. This paper will present the results from the first application of the ‘Best of Best' (BoB) methodology in Mexico. This successful application enforces the idea that by coupling re-engineering practices to develop a more creative well design along with stringent performance monitoring; any field performance can be improved to deliver stellar results.


2021 ◽  
Author(s):  
Mohammad Soroush ◽  
Mahdi Mahmoudi ◽  
Morteza Roostaei ◽  
Hossein Izadi ◽  
Seyed Abolhassan Hosseini ◽  
...  

Abstract In wake of the biggest oil crash in history triggered by the COVID-19 pandemic; Western Canada in- situ production is under tremendous price pressure. Therefore, the operators may consider shut in the wells. Current investigation offers an insight into the effect of near-wellbore skin buildup because of such shut-in. A series of simulation studies was performed to quantitatively address the impact of well shut-in on the long-term performance of well, in particular on key performance indicators of the well including cumulative steam to oil ratio and cumulative oil production. The long-term shut-in contributes to three main modes of plugging: (1) near-wellbore pore plugging by clays and fines, (2) scaling, and (3) chemical consolidation induced by corrosion. A series of carefully designed simulations was also utilized to understand the potential of skin buildup in the near-wellbore region and within different sand control devices. The simulation results showed a higher sensitivity of well performance to shut-in for the wells in the initial stage of SAGD production. If the well is shut in during the first years, the total reduction in cumulative oil production is much higher compared to a well which is shut-in during late SAGD production life. As the induced skin due to shut-in increases, the ultimate cumulative oil production drops whose magnitude depends on well completion designs. The highest effect on the cumulative oil production is in the case of completion designs with flow control devices (liner deployed and tubing deployed completions). Therefore, wellbore hydraulics and completion design play key roles in the maintenance of uniform inflow profile, and the skin buildup due to shut-in poses a high risk of inflow problem and increases the risk of hot-spot development and steam breakthrough. This investigation offers a new understanding concerning the effect of shut-in and wellbore skin buildup on SAGD operation. It helps production and completion engineers to better understand and select candidate wells for shut-in and subsequently to minimize the skin buildup in wells.


2021 ◽  
Vol 6 (4) ◽  
pp. 123-130
Author(s):  
Aleksandr V. Korytov ◽  
Oleg A. Botkin ◽  
Aleksandr V. Knyazev ◽  
Petr V. Zimin ◽  
Dmitriy P. Patrakov ◽  
...  

Background. The study performed by Rosneft employees shown in this paper demonstrates approach and analytical methods that allows to forecast oil production at the level of minimal infrastructure units. These approaches are used to forecast long-term oil production and predict infrastructure blockage. The approach was partially automated by the authors. This made it possible to testing at giant Krasnoleninskoye oilfield. Aim. The study was performed in order to develop and test an approaches to forecast oil production of large oil fields with high detail levels. Materials and methods. Common methods of decline curve analysis and water-into-oil curve analysis were used in this work to analyze the precondition. The main feature of the approach is the analysis of precondition at the level of large well clusters and transfer it to the level of wells. Some of the actions were automated by new proprietary software and were tested at the giant brown field. The software was integrated with the corporate database. Results. An author’s approach has been developed. The approach allows to forecast oil production at the level of infrastructure units using analytical methods. Oil production of the giant brown field with high detail levels were forecasted using the proposed approaches and developed software. Conclusions. The results show that the developed approaches and software can be used to forecast mediumand long-term performance of producing oil fields in the conditions of existing external and infrastructural constraints.


2021 ◽  
Author(s):  
Tao Wu ◽  
Hanzhi Fang ◽  
Hu Sun ◽  
Feifei Zhang ◽  
Xi Wang ◽  
...  

Abstract Unconventional reservoirs such as shale and tight sandstones that with ultra-low permeability, are becoming increasingly significant in global energy structures (Pejman T, et al., 2017). For these reservoirs, successful hydraulic fracturing is the key to extract the hydrocarbon resources efficiently and economically. However, the intrinsic mechanisms of fracturing growth in the tight formations are still unclear. In practice, fracturing design mainly depends on hypothetical models and previous experience, which leads to difficulties in evaluating the performance of the fracturing jobs. Therefore, an improved method to optimize parameters for fracturing is necessary and beneficial to the industry. In this paper, a data-driven approach is used to evaluate the factors that dominate the production rate from tight sandstone formation in Changqing Field which is the largest oil field in China. In the model, the input parameters are classified into two categories: controllable parameters (e.g. stage numbers, fracturing fluid volume) and uncontrollable parameters (e.g. formation properties), and the output parameter is the accumulated oil production of the wells. Data for more than 100 wells from different formations and zones in Changqing Field are collected for this study. First, a stepwise data mining method is used to identify the correlations between the target parameter and all the available input parameters. Then, a machine learning model is developed to predict the well productivity for a given set of input parameters accurately. The model is validated by using separate data-sets from the same field. An optimize algorithm is combined with the data-driven model to maximize the cumulative oil production for wells by tuning the controllable parameters, which provides the optimized fracturing design. By using the developed model, low productivity wells are identified and new fracturing designs are recommended to improve the well productivity. This paper is useful for understanding the effects of designed fracturing parameters on well productivity in Changqing Oilfield. Furthermore, it can be extended to other unconventional oil fields by training the model with according data sets. The method helps operators to select more effective parameters for fracturing design, and therefore reduce the operation costs for fracturing and improve the oil and gas production.


2020 ◽  
Vol 10 (4) ◽  
pp. 1497-1510
Author(s):  
Mohamed Mahmoud ◽  
Ahmed Aleid ◽  
Abdulwahab Ali ◽  
Muhammad Shahzad Kamal

AbstractThe main objectives of this paper are to assess the long-term and short-term production based on both reservoir parameters and completion parameters of shale gas reservoirs. The effects of the reservoir parameters (permeability and the initial reservoir pressure) and completion parameters (fracture geometry, stimulated reservoir volume, etc.) on the short-term and long-term production of shale gas reservoirs were investigated. The currently used approach relies mainly on the decline curve analysis or analogs from a similar shale play to forecast the gas production from shale gas reservoirs. Both these approaches are not satisfactory because they are calibrated on short production history and do not assess the impact of uncertainty in reservoir and well data. For the first time, this study integrates initial production analysis, probabilistic evaluation, and sensitivity analysis to develop a robust workflow that will help in designing a sustainable production from shale gas plays. The reservoir and completion parameters were collected from different available resources, and the probability distributions of gathered uncertain data were defined. Then analytical models were used to forecast the production. Two well evaluation results are presented in this paper. Based on the results, completion parameters affected the short-term and long-term production, while the reservoir parameters controlled the long-term production. Long-term well performance was mainly controlled by the fracture half-length and fracture height, whereas other completion and reservoir parameters have an insignificant effect. Stimulation treatment design defines the initial well performance, while well placement decision defines well long-term performance. The findings of this study would help in better understanding the production performance of shale gas reservoirs, maximizing production by selecting effective completion parameters and considering the governing reservoir parameters. Moreover, it would help in accomplishing more effective stimulation treatments and define the potentiality of the basin.


2021 ◽  
Author(s):  
Mahmoud Abd El-Fattah ◽  
Ahmed Moustafa Fahmy ◽  
Hamed Wahaibi ◽  
Abdullah Shibli ◽  
Khaled Zuhaimi

Abstract One of the largest oil fields in the GCC was developed in the 1960's. The field was initially produced under natural depletion supplemented by gas injection. The high offtake rates led to a rapid displacement of the gas/oil contact; thus, the field has now been suffering from early gas/water breakthrough and uneven fluid influx along with the horizontal wells. The reservoir has been on production for more than 50 years. Water/gas breakthrough from fractures being the major challenge which negatively affects wells oil production rates. Applying technology which can manage water/gas breakthrough in a cost-effective manner whilst allowing increased oil production was a key goal from operators in this field. Passive Inflow Control Devices (ICD) were introduced to the global oil and gas market in mid/late-1990's, and the first generation of Autonomous ICD (AICD) that can help reduce more unwanted gas or water was first installed in 2007. ICD's successfully demonstrated that they could delay the gas and/or water breakthrough within horizontal wells, but they could not choke gas when the coning/gas-breakthrough occurred and along with limited abilities to stop unwanted water production. To help solve this problem, the Autonomous Inflow Control Devices (AICD-RCP) with a movable disc was introduced to the market and demonstrated reduction of gas production by 20-30% with similar gains in oil production[1]. In this paper, the newest generation of Autonomous Inflow Control Valve (AICV) technology is presented. The AICV technology has a movable piston that can close and reduce the unwanted gas and water production by up to 95%[2]. The application of AICVs discussed herein were deployed within several wells which had extremely high Gas Oil Ratio (GOR) and low oil production. The novel AICV technology can differentiate between fluid types based on viscosity and density. When undesired fluid (gas and/or water) starts to be produced, the AICV chokes the valve flow area gradually until completely shutting off, all without well intervention[3]. Well production performances are documenting the benefits of installing AICV completions. The results demonstrate the AICVs closing the zones with high gas production and favoring oil-rich zones. Majority of evaluated wells demonstrated clearly that the extremely high GOR was reduced; some wells have returned to solution GOR for more than two years, and at the same time, the daily oil production is increased.


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