Real-Time Evaluation of Carbon Dioxide Production and Sequestration in a Gas Field

2013 ◽  
Vol 16 (02) ◽  
pp. 134-143 ◽  
Author(s):  
M.. Aschehoug ◽  
C.S.. S. Kabir

Summary The production of a substantial fraction of carbon dioxide (CO2) in any hydrocarbon-gas stream poses a significant challenge in terms of separation and sequestration. Both environmental concerns and economic incentives encourage the operators to search for safe, cost-effective ways of disposing of CO2. This paper presents a case study in which a pragmatic solution of CO2 separation at surface and its disposal in a saline aquifer occur in close proximity to its source. A suite of both modern and classical analytical tools is used to understand the production behavior of individual wells. This understanding is imperative because production volume is dictated by the ability to dispose of the associated CO2 volumes to honor the fault-activation pressure limit. The analytical tool kit—transient-productivity index (PI), combined static and dynamic material-balance (MB) methods, and rate-transient analysis (RTA), among others—allowed for the rapid assessment of both the producing gas reservoir and the saline aquifer receiving the CO2 stream. The use of real-time data allowed a comprehensive assessment of in-place volumes for the source gas and the capacity of the aquifer. The injection of supercritical CO2 suggests that the terminal aquifer pressure has been reached by encountering less-than-expected storage volume and by the lowering of fracture-pressure gradient. On-time learning has allowed the asset team to search for alternative CO2-disposal solutions to ensure continuous gas production from this field.

2021 ◽  
Author(s):  
Bashirul Haq

Abstract Sour gas reservoirs are vital sources for natural gas production. Sulphur deposition in the reservoir reduces a considerable amount of gas production due to permeability reduction. Consequently, well health monitoring and early prediction of Sulphur deposition are crucial for effective gas production from a sour gas reservoir. Dynamic gas material balance analysis is a useful technique in calculating gas initially in place utilizing the flowing wellhead or bottom hole pressures and rates during the well's lifetime. The approach did not apply to monitor a producing gas's health well and detect Sulphur deposition. This work aims to (i) modify dynamic gas material balance equation by adding the Sulphur deposition term, (ii) build a model to predict and validate the issue utilizing the modified equation. A unique form of the flowing material balance is developed by including Sulphur residue term. The curve fitting tool and modified flowing gas material balance are applied to predict well-expected behaviour. The variation between expected and actual performance indicates the health issue of a well. Initial, individual components of the model are tested. Then the model is validated with the known values. The workflow is applied to active gas field and correctly detected the health issue. The novel workflow can accurately predict Sulphur evidence. Besides,the workflow can notify the production engineers to take corrective measures about the subject. Keywords: Sulfur deposition, Dynamic gas material balance analysis, Workflow


2012 ◽  
Vol 15 (03) ◽  
pp. 351-360 ◽  
Author(s):  
D.. Ismadi ◽  
C.S.. S. Kabir ◽  
A.R.. R. Hasan

Summary Estimating in-place volume associated with each well, leading to estimation of total reservoir in-place volume, is the cornerstone to any reservoir-management practice. Yet, conventional methods do not always lend themselves to routine applications, particularly when used in singular fashion. However, combining these methods on the same plot has considerable merit in that they converge to the same solution when material-balance (MB) -derived averagereservoir pressure is used in a volumetric system. This study presents a systematic procedure for estimating the gas-initially-in-place (GIIP) volume when real-time surveillance data of pressure, rate, and temperature are available at the wellhead. Specifically, we show that log-log diagnosis, followed by combined static- and dynamic-MB analysis and transient-productivity-index (PI) analysis, leads to consistent solutions. Thermodynamic behavior of fluids is also explored to ensure that converted pressures at the bottomhole and measured rates have consistency and accuracy for reservoir-engineering calculations. Layered systems were selected for this study because they represent most situations. Two synthetic cases probed issues pertaining to average-reservoir-pressure computation with the pseudosteady-state (PSS) approach, and two field examples validated the approach presented here.


2021 ◽  
Vol 64 (11) ◽  
pp. 793-801
Author(s):  
R. R. Kantyukov ◽  
D. N. Zapevalov ◽  
R. K. Vagapov

At the present stage of gas field development, the products of many mining facilities have increased content of corrosive CO2 . The corrosive effect of CO2 on steel equipment and pipelines is determined by the conditions of its use. CO2 has a potentially wide range of usage at oil and gas facilities for solving technological problems (during production, transportation, storage, etc.). Simulation tests and analysis were carried out to assess the corrosion effect of CO2 on typical steels (carbon, low-alloy and alloyed) used at field facilities. Gas production facilities demonstrate several corrosion formation zones: lower part of the pipe (when moisture accumulates) and top of the pipe (in case of moisture condensation). The authors have analyzed the main factors influencing the intensity of carbon dioxide corrosion processes at hydrocarbon production with CO2 , its storage and use for various technological purposes. The main mechanism for development of carbon dioxide corrosion is presence/condensation of moisture, which triggers the corrosion process, including the formation of local defects (pits, etc.). X-ray diffraction was used for the analysis of corrosion products formed on the steel surface, which can have different protective characteristics depending on the phase state (amorphous or crystalline).


2021 ◽  
Author(s):  
Ernesto Gomez Samuel Gomez ◽  
Raider Rivas ◽  
Ebikebena Ombe ◽  
Sajjad Ahmed

Abstract Background Drilling deviated and horizontal high-pressure, high-temperature (HPHT) wells is associated with unique drilling challenges, especially when formation heterogeneity, variation in formation thickness as well as formation structural complexities are encountered while drilling. One of the major challenges encountered is the difficulty of landing horizontal lateral within the thin reservoir layers. Geomechanical modeling has proven to be a vital tool in optimizing casing setting depths and significantly increasing the possible lateral length within hydrocarbon bearing reservoirs. This approach ultimately enhanced the production output of the wells. In a particular field, the horizontal wells are constructed by first drilling 8 3/8" hole section to land about 5 to 10’ into the impervious cap rock just above the target reservoir. The 7" casing is then run and cemented in place, after which the horizontal hole section, usually a 5 7/8" lateral, is drilled by geosteered within the target reservoir to access its best porosity and permeability. Due to the uncertainty of the cap rock thickness, setting the 7" liner at this depth was necessary to avoid drilling too deep into the cap rock and penetrating the target reservoir. This approach has its disadvantages, especially while drilling the 5-7/8" lateral. Numerous drilling challenges were encountered while drilling the horizontal lateral across the hard cap rock. like severe wellbore instability, low ROP and severe drillstring vibration. To mitigate the challenges mentioned above, geomechanical modelling was introduced into the well planning process to optimize the 8 3/8" hole landing depth within the cap rock, thereby reducing the hard caprock interval to be drilled in the next section. Firstly, actual formation properties and in-situ rock stress data were obtained from logs taken in previously drilled wells in the field. This information was then fed into in the geomechanical models to produce near accurate rock properties and stresses values. Data from the formation fracture strength database was also used to calibrate the resulting horizontal stresses and formation breakdown pressure. In addition to this, the formation pore pressure variability was established with the measured formation pressure data. The porosity development information was also used to determine the best landing depths to isolate and case-off the nonreservoir formations. Combined with in-depth well placement studies to determine the optimal well trajectory and wellbore landing strategy, geomechanical modelling enabled the deepening of the 8 3/8" landing depth without penetrating the hydrocarbon reservoir. The geomechanical models were also updated with actual well data in real time and allowed for the optimization of mud weight on the fly. This strategy minimized near wellbore damage across the reservoir section and ultimately improved the wells productivity index. Deepening of the 8 3/8" landing depth and minimizing the footage drilled across the hard and unstable caprock positively impacted the overall well delivery process from well planning and drilling operations up to production. The following achievements were realized in recent wells where geomechanical modelling was applied: The initiative helped in drilling more stable, in-gauge holes across the reservoir sections, which were less prone to wellbore stability problems during drilling and logging operations.Downhole drilling tools were less exposed to harsh drilling conditions and delivered higher performance along with longer drilling runs.Better hole quality facilitated the running of multistage fracture completions which, in turn, contributed to increase the overall gas production, fulfilling the objectives of the reservoir development team.The net-to-gross ratio of the pay zone was increased, thereby improving the efficiency of the multistage fracture stages, and allowing the reservoir to be produced more efficiently.


INSIST ◽  
2018 ◽  
Vol 3 (2) ◽  
pp. 154
Author(s):  
Panca Suci Widiantoro ◽  
Astra Agus Pramana ◽  
Putu Suarsana ◽  
Anis N Utami

Production optimization in mature field water drive gas reservoir is not easy especially when water already breakthrough in producing wells. An integrated reservoir study is needed to get reliable strategy to optimize production of water drive gas reservoir.   This research presents the integrated reservoir study of Lower Menggala (LM) Gas Field which is located Central Sumatera Basin, Riau Province. LM had been produced since 1997, current RF are 55%, which is quite high for water drive gas reservoir. The current gas rate production is about 1.97 MMscfd with high water production around 4250 BWPD, consequently some of wells suffered liquid loading problem   This research comprises of well performance analysis, estimate OGIP, aquifer strength of the reservoir by using conventional material balance method and modern production analysis method then conduct dynamic reservoir simulation to identify the best strategy to optimize gas production. Economic analysis also be performed to guide in making decision which scenario will be selected. DST analysis on DC-01 well defined reservoir parameter, boundary and deliverability which are P*= 2520 psia, k= 229 mD, Total skin= 8, detected sealing fault with distance 175 m, and AOF 45 MMscfd. Conventional material balance method gave OGIP 22.7 BScf, aquifer strength 34 B/D/Psi, whereas modern production analysis estimated OGIP 22.35 BScf, aquifer strength 34 B/D/psi. Those two method shows  good consistency with OGIP  volumetric calculation with discrepancy OGIP value +/- 1%. Six (6) scenario of production optimization has been analyzed, the result shows that work over in two wells and drilling of  1 infill well (case 6) achieve gas recovery factor up to 75.2%, minimal water production and attractive economic result


2021 ◽  
Author(s):  
Emmanuel Udofia

Abstract Well testing could be described as a process required to calculate the volumes of (oil, water and gas) production from a well in a bid to identify the current state of the well. Amongst other things, well testing aims to provide information for effective Well, Reservoir and Facility Management. Normally, as a means of well performance health-check, reconciliation factor (RF) is generated by comparing the fiscal production volume against the theoretical well test volume. Experiences from the Coronavirus pandemic has brought about the new normal into well test execution. In deepwater environment, the process of well testing is more challenging and this paper aims to address these challenges and propose optimum well test frequency for deepwater operations. It is usually required that routine well test be conducted once every month on all flowing strings, this is for statutory compliance and well health-check purposes. However, in deepwater environment, it is difficult to comply with this periodic well test requirement mainly due to production flow line slugging, plant process upset and/or tripping resulting in production deferment and operational risk exposure. Furthermore, to carry out well test in deepwater operation, production cutback is required for flow assurance purpose and this usually results in huge production deferment. In this field of interest, this challenge has been managed by deploying a data-driven application to monitor production on individual flowing strings in real-time thereby optimizing the frequency of well test on every flowing well. Varying rate well test data are captured and used to calibrate this tool or application for subsequent real-time production monitoring. This initiative ensures that all the challenges earlier mentioned are managed while actually optimizing the frequency of testing the wells using intelligent application which serves as a ‘virtual meter’ for testing all producing wells in real time. As mentioned, well testing in most deepwater assets remain a big challenge but this project based field experience has ensured effective well testing operation resulting in reduction of production deferment and safety exposure during plant tripping whilst optimizing frequency of testing the wells. Following this achievement of the optimized well test to quarterly frequency in this field in Nigerian deepwater, recommendation from this paper will assist other deepwater field operators in managing routine well testing operation optimally.


2015 ◽  
Author(s):  
Musab Khudiri ◽  
Faisal Al-Sanie ◽  
Ramzi Miyajan ◽  
Ali Wuhaimed ◽  
Maan Hawi ◽  
...  

Author(s):  
Burke Pond ◽  
Rick Barlow ◽  
Sooban Kamal

The operation of Enbridge’s pipeline system is continuously monitored by a leak detection system termed the Material Balance System (MBS). The MBS is not only a regulatory requirement; it helps minimize the financial and environmental damages that could result from an oil leak. A team of MBS experts provides 24/7 support to Enbridge’s control centre, which manages pipeline operations. When MBS predicts or detects any hydraulic abnormality in the pipeline, it alerts the operations’ staff. Though the operators do some basic analyses, such abnormal situations are usually referred to the support team. The idea of the intelligent alarm analyzer is to provide a tool to analyze and present the most probable cause of the alarm. The human knowledge of MBS alarm analysis is transferred into a soft knowledge base, which is then used in combination with the real-time data to analyze the alarm causes. Logic was developed to identify a group of alarms caused by a single reason, which was important from the performance point of view as a set of alarms can result from one event. In parallel, some basic rules were designed to implement the procedure for analyzing these alarms. A detailed study of some typical alarm scenarios was done to build an example knowledge base. The “event” triggers the alarm analyzer, which uses the real-time data and the knowledge base to go through an extensive series of logical evaluations and mathematical manipulations (called “tests”) to decide on the probable cause of the alarms. The next task was to combine the power of computational techniques and human understanding to implement possible scenarios. At this stage more complex and realistic rules have been developed to facilitate real-time alarm analyses. The paper will include an example scenario of how the tool could be applied to a production system. The alarm analysis system described in this paper is currently being tested for production use later this year. Once in production, additional tuning and refinement of the tool will be a continuing process.


2009 ◽  
Vol 14 (2) ◽  
pp. 109-119 ◽  
Author(s):  
Ulrich W. Ebner-Priemer ◽  
Timothy J. Trull

Convergent experimental data, autobiographical studies, and investigations on daily life have all demonstrated that gathering information retrospectively is a highly dubious methodology. Retrospection is subject to multiple systematic distortions (i.e., affective valence effect, mood congruent memory effect, duration neglect; peak end rule) as it is based on (often biased) storage and recollection of memories of the original experience or the behavior that are of interest. The method of choice to circumvent these biases is the use of electronic diaries to collect self-reported symptoms, behaviors, or physiological processes in real time. Different terms have been used for this kind of methodology: ambulatory assessment, ecological momentary assessment, experience sampling method, and real-time data capture. Even though the terms differ, they have in common the use of computer-assisted methodology to assess self-reported symptoms, behaviors, or physiological processes, while the participant undergoes normal daily activities. In this review we discuss the main features and advantages of ambulatory assessment regarding clinical psychology and psychiatry: (a) the use of realtime assessment to circumvent biased recollection, (b) assessment in real life to enhance generalizability, (c) repeated assessment to investigate within person processes, (d) multimodal assessment, including psychological, physiological and behavioral data, (e) the opportunity to assess and investigate context-specific relationships, and (f) the possibility of giving feedback in real time. Using prototypic examples from the literature of clinical psychology and psychiatry, we demonstrate that ambulatory assessment can answer specific research questions better than laboratory or questionnaire studies.


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