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Search Mediterranean Sea: production test
A Technically Rigorous and Fully Automated System for Performance Monitoring and Production Test Validation
Bruni, Thomas (ENI E&P Division) | Lentini, Amelia (ENI E&P Division) | Ventura, Stefano (ENI E&P Division) | Gheller, Ruggero (ENI E&P Division) | Maybee, Charles A. (Landmark Graphics Corporation) | Pinedo, Jorge E. (Landmark Graphics Corporation)
...SPE 84881 A Technically Rigorous and Fully Automated System for Performance Monitoring and Production Test Validation Thomas Bruni, SPE, ENI E&P Division, Amelia Lentini, ENI E&P Division, Stefano Ventura,...tation at the SPE International Improved Oil Recovery providing a more reliable and time effective production test Conference in Asia Pacific held in Kuala Lumpur, Malaysia, 20-21 October 2003. validation process...position of the Society of Petroleum Engineers, its officers, or members. Papers presented at from production tests, dependable ...
... Workflows strings and calculations to perform. Rigorous system analysis The major problem that the production engineers were models for each producing string were constructed and facing with the old system was...h as locating, exporting and reformatting of data consumed daily performance monitoring and one for production valuable engineering time from beneficial activities like ...test validation. analysis and diagnosis of well performance. Engineering Daily performance surveillance:...
...SPE 84881 3 analysis model and should be reflective of the last valid Field Examples production test. The system was deployed to ...production/gathering centers: 1. Gas Plant Network. It comprises seven offshore gas ...Production test validation: Utilizing the string fields, 14 platforms and about 180 ...
Abstract This paper describes the integration between a dynamic surveillance tool and a system analysis tool to provide the surveillance engineer with a new, fully automated and technically rigorous system, capable of true performance monitoring and reliable production test validation. The combination of the software tools and workflows resulted in an innovative Production Management and Optimization system (PROMO), with new and extended capabilities beyond those of either of the stand-alone packages. Algorithms were defined in order to automatically compare actual and modeled production (taking into account FTHP variations) on a daily basis. Additionally, as new production test data becomes available, the system can automatically display it on a calibrated IPR plot for fast and rigorous validation. The system has also been designed such that when a new well test is approved and validated, the IPR curve will be automatically re-calibrated to honor the new performance measurements. In principle no gas or oil field is outside the scope of such an application. Once an appropriate interface is set up to allow for data exchange between the surveillance and system analysis tools, it is a matter of building the appropriate processes that will yield the most beneficial results in terms of production optimization and data validation. The addition of data linkages to corporate data warehouses results in a system that requires little maintenance of input parameters and is always up-to-date with respect to the available data. The PROMO system, currently deployed in one gas plant (comprising of seven offshore gas fields, 14 platforms and 180 production strings) and one oil plant (comprising of two onshore oil fields and 10 production strings), is allowing the production engineers to easily identify under-performing strings (completions) and promptly intervene. In addition to providing a more reliable and time effective production test validation process, the engineer can fully analyze current well performance with daily, historical and forecasted data. Additional benefits include calculation of historic SBHP's from production tests, dependable production allocation (with great benefit for overall field management and reservoir modeling) and considerable time savings as pertinent data is automatically (as opposed to manually) handled and used in the system analysis algorithms. Introduction Production surveillance and reliable allocation play a major role in the efforts to optimize and maximize production from a field. Many software solutions exist to monitor actual performance variables of well and field systems. Just as important is performance modeling through system analysis methods and again the relevant commercial packages are several and well established. However, the added value from combining the two systems (production monitoring and system analysis) has not been entirely captured to date - at least not to its full potential. The operator involved in this project was no exception. Production data was stored in two corporate databases (daily and monthly production) and monitored using desktop spreadsheets. The inherent drawbacks to this surveillance process were redundant, static and localized subsets of corporate databases, no standardized or transferable workflows or formats, lack of strict data quality control and integrity, and poor fit-for-purpose of the spreadsheet software. Additionally the overall system was lacking the integrated system analysis capabilities to effectively monitor string/well performance. The necessary system analysis workflows were being achieved using an industry standard software tool, but at the expense of manual data entry. An obvious problem with such a disjointed system was the lack of communication between the two tool sets, resulting in lengthy production data handling and formatting before data could be returned to the system analysis software for the computations. Also there was no mechanism in place to return the system analysis results for use in the surveillance process.
- North America > United States > Texas > Coleman County (0.24)
- Asia > Middle East > Israel > Mediterranean Sea (0.24)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Well performance, inflow performance (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Drillstem/well testing (1.00)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring (1.00)
- Data Science & Engineering Analytics > Information Management and Systems (1.00)
Substantiation of Reservoir Lateral Hydraulic Connectivity Based on Integrated subsurface and Production test result - Niger Delta Field Experience
Adepoju, Yaqub (SPDC Ltd.) | Anyaehie, James (SPDC Ltd.) | Ogbuli, Andrew (SPDC Ltd.) | Balogun, Olalekan (SPDC Ltd.) | Awa, Chukwunweike (SPDC Ltd.) | Mora-Glukstad, Miguel (SPDC Ltd.) | Kakayor, Omagbemi (SPDC Ltd.)
...71-MS Substantiation of Reservoir Lateral Hydraulic Connectivity Based on Integrated subsurface and Production test result - Niger Delta Field Experience Yaqub Adepoju, James Anyaehie, Andrew Ogbuli, Olalekan Balog...astern fault block, modelled as a reservoir compartment, and subsequently carry out an interference test to establish the lateral hydraulic connectivity of the reservoirs. A new seismic data was acquired ... hydraulic continuity, a multidisciplinary integrated study was conducted using all available data (production tests, Seismic and Petrophysical data). This paper covers the multi-disciplinary work carried out t...
...c continuity, a multidisciplinary integrated study was conducted using all available data including production test result, Seismic and Petrophysical data. With a better seismic image, this integration effort improv...eduction in capital exposure by the elimination of the drilling of the appraisal well, interference test and reduction in the well count required to optimally develop the reservoirs. Structural Interpret...
...-178371-MS 5 Figure 5--B4000X correlation panel showing reservoir continuity and sand development Production Test Analysis Result - A1000X and B4000X Reservoirs Multi Rate Well tests (flowing and build up) was ca...
Abstract Field X is one of SPDC's major gas fields located onshore of Nigeria with six well penetrations and two key reservoirs, A1000X and B4000X,. The field is covered by a 1992 3D seismic reprocessed PSDM with relatively poor imaging quality. This caused uncertainties with respect to the interpretation of possible intra-reservoir fault compartmentilization. These intra-reservoir faults are on the footwall of two major southern and eastern boundary faults. To optimally develop these reservoirs, it was proposed to drill an appraisal well in the eastern fault block, modelled as a reservoir compartment, and subsequently carry out an interference test to establish the lateral hydraulic connectivity of the reservoirs. A new seismic data was acquired and processed to resolve the uncertainties associated with the poor imaging quality of the 1992 seismic. The interpretation of the new seismic showed similar structural trend, albeit with better clarity of the subsurface images in the fault shadow zones. It also showed continuous seismic reflection loops suggesting a more better lateral reservoir connectivity To better understand the reservoir lateral hydraulic continuity, a multidisciplinary integrated study was conducted using all available data (production tests, Seismic and Petrophysical data). This paper covers the multi- disciplinary work carried out to establish the lateral connectivity of the reservoirs and its significant cost reduction to the total project cost.
- Africa > Nigeria > Niger Delta (0.41)
- North America > Canada > Saskatchewan (0.40)
- Asia > Middle East > Israel > Mediterranean Sea (0.40)
- Africa > Nigeria > Gulf of Guinea > Niger Delta (0.40)
...SPE-173394-MS Improving Multiphase Choke Performance Prediction and Well Production Test Validation Using Artificial Intelligence: A New Milestone Mohammed D. AlAjmi, Saudi Aramco; Sulaim...gment of SPE copyright. Abstract Converting data to actionable information through continuous oil production monitoring is a fundamental part of any ...production optimization strategy. The development of Intelligent Field technology has remarkably contributed t...
...us Investigators of high wellhead flowing pressures, or sustaining Investigator C m n economical production rate limits set by the regulatory authorities. Gilbert 10 0.546 1.84 Baxendell 9.56 0.546 1.93 Si...nce the oil production rate is extremely sensitive Ros 17.40 0.500 2 to changes in the choke size, modeling flow Achong... 3.82 0.650 1.88 through chokes is vitally important for oil production Pilehavari 46.67 0.313 2.11 simulation. In fact, having a robust choke performance model consider...
... upstream pressure, temperature, gas-oil ratio, and water cut all measured or collected during well production rate ...test operations. A subcritical dataset...
Abstract Converting data to actionable information through continuous oil production monitoring is a fundamental part of any production optimization strategy. The development of Intelligent Field technology has remarkably contributed to the upgrading of production surveillance framework and provided an extended access to real-time data. This same technology is still in its infancy when it comes to multiphase mass metering and field practicality issues. As for conventional fields where the unavailability of continuous data flow is not considered out of norm, the high uncertainty in oil production rate estimation and allocation is very well expected. The main source of this uncertainty is the reliance on sporadic welltest data and empirical multiphase flow correlations to allocate liquid production rate. Critical and subcritical multiphase flow choke performance is predicted using well-known correlations that are based on specific datasets characterized by a specific field or hydrocarbon type. Case studies where those correlations are matched with different production data and used later to predict the choke performance are present in the literature. Yet, the oil industry is faced with many challenges because of the limited accuracy of those predictions. The complexity of multiphase flow behavior and the irregularities in operational conditions can explain such low capability of those correlations particularly on field data. Artificial intelligence (AI) tools and techniques for so-called artificial neural networks, fuzzy logic and functional networks were employed to develop data-driven oil flow rate computational models for both critical and subcritical flow conditions. These AI models were trained and tested exploiting 595 production rate tests from 31 different wells. The prediction results showed a strong correlation with actual field data and promised a reliable tool/methodology to estimate oil flow rate as a function of operational conditions and choke size. This paper presents an engineering look at the inclusion of AI data-driven models in the production surveillance system to enhance welltest data validation and reduce the uncertainties in production allocation.
...SPE 93275 Application of Fuzzy Logic for Determining Production Allocation in Commingle ...Production Wells B. Widarsono and H. Atmoko, Lemigas; W. Robinson IV and I.P. Yuwono, PT CPI; F. Saptono, Tun...repared for presentation at the 2005 SPE Asia Pacific Oil & Gas Conference In managing a commingle production well, knowledge over and Exhibition held in Jakarta, Indonesia, 5-7 April 2005. ...
...idered to contribute to the total well 'medium' and 'high'. This makes fuzzy logic suitable for the production in exactly the same proportion. This certainly nature of data the geophysicists, geologists, and re...common occurrences in which there are engineers has to evaluate [1]. possibilities that decline in production rate are caused by rise in water cut. Secondly, the properties mentioned above are The relationship...fecting factors on the individual layer's described in forms of fuzzy IF-THEN rules. Given a set of production potential. input-output patterns, many similar fuzzy rules can be derived, in an overlapping manner...
...SPE 93275 3 Considering the production log's absence, attention is given to LOW porosity 18% the ...production test on single layer as the primary source of information regarding the layer's contribution capacity. M...EDIUM 18% porosity 30% Apart from the production tests data there is also swab ...
Abstract For oil or gas fields with stratified reservoir layers, detailed productioncontribution for individual layer is always desired.Unfortunately, insome particular cases, production wells are completed following commingledscheme. This is worsened further if only very few production tests arerun for the field.This is the case for the Central Sumatera field withits 95 commingled production wells, among which only a few had undergoneproduction tests and none of them have ever undergone productionlogging.Problems rise when the occassion came in which detailedproduction contribution from individual reservoir layer is required for thefield's reservoir simulation modeling and productionevaluation/prediction. This paper presents an approach to solve the problem.The approach isbasically based on the application of soft computing (Fuzzy Logic) toinvestigate pattern of relationships between production contribution of layersin commingle wells and rock petrophysical data as well as other relevantgeological/engineering data.For the purpose, thirteen wells (key wells)that have production tests are assigned, among which three wells are assignedfor checking the validity of the recognised pattern.Using the validatedmost valid pattern, individual layer's production allocation for other wellsare determined with well-log analysis data as the major input. Result estimates for the candidate wells are better compared to resultsproduced by the conventional method of productivity index (PI)analogy.The resulted variation in water cut and separate oil and watersplit factors appear to be more realistic from any point of view. Introduction In managing a commingle production well, knowledge over productioncontribution of individual sand layer is always desired.The commonpractice performed during drilling and production activities of a productionwell is through the use of well testing/production testing and/or productionlogging. From the test, fluid dynamic data such as total liquid rate, water cut, and gas cut of an individual layer are produced.However, costand time efficiency is always used as the reason for not conducting suchtests. Therefore, even though such tests are always regarded as theprimary source of proof, an alternative means that can be used to provideestimates is always desired. Ideas of establishing a method that can provide illustration over productioncontribution of all layer(s) always exist.Certainly, there are approachesto serve the purpose such as productivity index (PI)/transmissibility analogyand petrophysical approach through fractional flow measurement in corelaboratory. However, those approaches are often considered inadequate foraccommodating various factors that may influence production contribution of aproductive layer. To materialize the requirement stated above, an indirect approach in theform of pattern recognition/modeling was taken.This approach was taken inorder to model relations between various factors in wellbore and productioncontribution of reservoir layers without being trapped by the certaincomplexity that may occur in any mathematical expressions trying to explain therelationships.For the purpose, fuzzy logic (a form of artificialintelligence) has been used.The choice is actually based on its capacityto accommodate both numeric and non-numeric data, since it is considered thatsome non-numeric data such as lithology and pore system also have someinfluence on production contribution.
- North America > United States > Texas (0.28)
- Asia > Indonesia (0.28)
- Asia > Middle East > Israel > Mediterranean Sea (0.24)
- Asia > Indonesia > Sumatra > Riau > Central Sumatra Basin > Rokan Block > Rokan Block > Bekasap Field > Menggala Formation (0.93)
- Asia > Indonesia > Sumatra > Riau > Central Sumatra Basin > Rokan Block > Rokan Block > Bekasap Field > Bekasap Formation (0.93)
- Asia > Indonesia > Sumatra > Riau > Central Sumatra Basin > Rokan Block > Rokan Block > Bekasap Field > Bangko Formation (0.93)
- Asia > Indonesia > Sumatra > Riau > Central Sumatra Basin > Rokan Block > Rokan Block > Bangka Field (0.93)
- Reservoir Description and Dynamics > Reservoir Characterization (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management (1.00)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring > Production logging (1.00)
- Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)
...SPE 110574 Success Stories in Onshore Production Surveillance and Optimization David F. Deaton, SPE, Halliburton Digital & Consulting Solutions, an... well as This paper was prepared for presentation at the 2007 SPE Annual Technical Conference and production strategies. Exhibition held in Anaheim, California, U.S.A., 11-14 November 2007. This paper was se... Society of Petroleum Engineers, its officers, or members. Papers presented at processes from mere production monitoring to enhanced SPE meetings are subject to publication review by Editorial Committees of t...
...nformation about 2. Data not integrated or filtered to support decisions reservoir characteristics, production operations, workflow and 3. High rate of ...production due to high energy demand performance, historical issues, data sources and optimization 4. Monitori...s tools. Questions in the survey were logically grouped into 5. Lack of readily accessible current production data categories to summarize the topic, and to facilitate the review, 6. Lack of data that can be u...
...or types of asset groupings within the Asset team. - Views and analysis of single and multiple well production, - Primary fields and locations incremental ...test data, pattern groups, and - Major field staffing of reservoir and ...production engineers decline curves - Current surveillance work flows and data flows - Ability to integrate e...
Abstract This paper presents the assessment methodology, technology, data sources, workflows, critical factors and intermediate results of Marathon Oil Company's production surveillance solutions implemented within two major asset teams, Permian Basin and East Texas. It is represented as a model for operators implementing digital oilfields, i-fields, or automation to improve the surveillance aspect of their production operations. The paper presents an asset-based collaborative project process for needs assessment, a surveillance solution for linking and visualizing production data, a workflow definition process, and a mentoring approach on the solution and workflow to insure successful implementation and value realization. Introduction Many owners and operators of North American oil and gas assets aim to improve asset productivity and return on investment through better production surveillance. These efforts have taken on increased importance due to an explosion of data sources, shrinking of the work force, maturing North American fields and associated challenges of pressure depletion, water production, and equipment failures. The typical production surveillance process consists of monitoring: oil, gas and water production rates against time and cumulative volume; downhole and surface pressures; flowing and artificial lift efficiency; downtime events and causes; any associated patterns (injection, fracture trends, etc.). The compilation of this data is then analyzed against test rates and the latest forecast or decline curve analysis, followed by field adjustments to optimize reserve recovery as well as production strategies. Through workflow-based value-analysis improvement projects, Marathon engineers are transforming their work processes from mere production monitoring to enhanced surveillance and optimization. They are on the way to achieving many benefits from these improvements, including increased production and reserves recovery, reduced time to identify problem wells, lower OPEX cost, timely correction of allocation problems, and integrated surface and subsurface data and operations. Traditionally, surveillance processes have been ruled by spreadsheets used to extract production and real-time data, manipulated and converted into correlations, tables, trends and charts. Following this approach, reservoir and production engineers spend an estimated fifty to seventy percent of their time finding, gathering and managing the data. This paper discusses projects recently conducted across Marathon's North American asset teams which focus on reversing this trend, allowing engineers to link directly to production data, and focus the majority of their time on data analysis and optimization of production operations. These projects used a proven methodology and technology consisting of:an asset-focused collaborative process for identifying and ranking the current workflows, data management, challenges and opportunities within production surveillance; a standardized solution for live-linking, visualizing, trending, correlating, analyzing and seamlessly linking production, process, intervention and equipment data; and effective surveillance workflow definition and solution mentoring for engineer
- North America > United States > Texas (1.00)
- Asia > Middle East > Israel > Mediterranean Sea (0.24)
- North America > United States > Texas > Permian Basin > Yeso Formation (0.99)
- North America > United States > Texas > Permian Basin > Yates Formation (0.99)
- North America > United States > Texas > Permian Basin > Wolfcamp Formation (0.99)
- (21 more...)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Drillstem/well testing (1.00)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring (1.00)
- Data Science & Engineering Analytics > Information Management and Systems (1.00)
- Production and Well Operations > Well Operations and Optimization > Produced water management and control (0.76)
...Society of Petroleum Engineers SPE 27975 Practical Well Test Interpretation Louis Mattar, Fekete Assocs. Inc. SPE Member Copyright 1994, Society of Petroleum...idence must be rejected, ignored or explained away. It is the responsibility of the analyst to Well Test Interpretation involves much more than integrate all these perspectives of the reservoir in order P...means incorporating The same analogy applies within each discipline. For geological information and production information; example in the field of pressure analysis, Pressure adjusting the measured data to res...
...2 PRACTICAL WELL TEST INTERPRETATION SPE 27975 the broader perspective of Well ...Test Interpretation gauge or a strain gauge. Mattar et al (reference 1) give (W.T.I.). In the rest of th...0 kPa, and independent measurements show the strain Figure 1 represents synthetic data of a buildup test gauge to be the correct one. [The quality of service is (150 hr. flow 31 hr. shut-in) as published ...
...may be totally for example, what is the true reservoir pressure? did inappropriate for the modified test, and much needed the injection create a hydraulic fracture which heals valuable data may be missed ...tion for the periodicity observed on the buildup pressure gets! This strange observation is readily test of a dry gas well shown in Figure 13. Both explained if it is recognized that the recorder is elect...and the recorder run depth is slowly filling up with water 10. Non-Unique Solutions: throughout the test. If the pressure at the end of the ...
Abstract Well Test Interpretation involves much more than Pressure Transient Analysis. It includes scrutinizing the field notes, the surface operations, the equipment and the well bore configuration. It means incorporating geological information and production information; adjusting the measured data to reservoir conditions and accounting for multiphase effects both in the well bore and in the reservoir; recognizing that well bore effects during a buildup are different from those during a drawdown; in short, integrating the practical issues with the theoretical analysis. Field examples will be presented to illustrate these effects. Ignoring these effects can lead to the wrong pressure transient analysis. Introduction Reservoir engineering integrates many "looks" into the reservoir; for example core analysis, log analysis, pressure analysis and production analysis. Each one of these gives its own view into the reservoir. Some only investigate a few inches (core, logs) while others reflect a much larger (100's of feet) radius of investigation (pressure, production). The "looks" can be supportive of each other and fit in with other "looks" into the reservoir, such as geology or seismic interpretations. However, quite often, these "looks" can be contradictory of each other, in which case some of the evidence must be rejected, ignored or explained away. It is the responsibility of the analyst to integrate all these perspectives of the reservoir in order to arrive at the best possible interpretation. The same analogy applies within each discipline. For example in the field of pressure analysis, Pressure Transient Analysis (P.T.A.) must be viewed as being only part of the picture, not the whole picture. Well Test Interpretation (W.T.I.) must encompass the field notes describing how the test was conducted, previous tests, initial and final static gradient, the well bore configuration, multi-phase aspects in the wellbore, wellbore dynamics (references 1, 2 and 3), material balance and production information, in addition to P.T.A. P.T.A. has become a very sophisticated tool, and because of its "advanced" nature, it tends to be placed on a pedestal, to the neglect of other more useful yet simpler information. For example, a P.T.A. on a flow and buildup test may indicate a dual porosity reservoir. While this may be the case (and there are many wellbore dynamics that may contra-indicate that), we may have overlooked the fact that static gradients before and after the test indicate depletion (a noneconomic reservoir-hence the dual porosity issue becomes a red herring). P. 175^
- North America > United States (0.29)
- Asia > Middle East > Israel > Mediterranean Sea (0.24)
...2 TEST AND E'JALuATrON METHUDOLOGY'FOR SCALE INHIBITOR EVALIJATl()NS r -- .. -·---·-·.. ·-·... ----·--...tains nUmerous references regarding other and simultaneously occuring prob-I ,ies.:ribing various test methods aimed at evaluat. lems that may dictate the application snd ing of scale inhibitors for t...s [l,6-22}. However, to our knowledge ther exists no publication dealing with Slight changes in test conditions will usually the subject of evaluating and/or analyzing the result in significant chang...
...3 SPE 16259 O.J. VETTER, V. KANDARPA, A. SCHALGE, M. STRATTON, E. VEITH 2. Many of the test procedures evaluate only certain 1. Degree of supersaturation (or scale forming scale inhibitor pro...equally pertinent and possibly more important inhibitor properties. 2. Temperature. 3. Many of the test procedures attempt to standardize 3. Pressure. on a limited number of ...test conditions. These tests do not simulate most of the pertinent 4. Time. field conditions. Inhibitor ...
... STRATTON, E. VEITH environmental variables and parameters are beneficial Naturally, the inhibitor test procedures become and others are detrimental to the fluid more complex and elaborate the more of t...hese conditions production from a subterranean reservoir. are actually considered and simulated in any laboratory ...test. Eventually, there will be a Table 1 lists some of the desired inhibitor characteristics. "point of...
Abstract This paper deals with an evaluation of scale inhibitor test methods used in the oil, gas and geothermal industries. To our knowledge there exists no other publication dealing with this subject of evaluating and analyzing the various test methods related to scale inhibitor evaluations. There are basically two different types of inhibitor test methods:Test methods aimed at solving a scale problem for routine, day-to-day field operations. Test methods aimed at solving a scale problem for temporary or intermittent field operations. Only the first type of test methods is described in this paper. Laboratory test procedures are used to evaluate and to rank scale inhibitors for field operations. Many of the tests use arbitrarily selected test conditions and many are based on unvarying test conditions. Others evaluate only the inhibitor efficiency without regarding other and simultaneously occurring problems that may dictate the application and usefulness of scale inhibitors in the field. Slight changes in test conditions will usually result in significant changes in the subsequent rankings of scale inhibitors. Each â??standardâ?¿ test may yield inhibitor data and rankings that are completely different from the data and rankings based on other â??standardâ?¿ tests. Any test procedure aimed at selecting an inhibitor for actual field use must consider actually encountered field conditions. Any test matrix should, as a minimum, include all the possible thermodynamic and at least some kinetic and hydrodynamic conditions encountered by the inhibitor in an actual field. The present paper discusses the advantages and disadvantages of the various scale inhibitor evaluation methodologies suited for the field operator. The relevancy of various evaluation methods for field applications is described. The paper is not oriented toward data obtained through previously or newly conducted inhibitor evaluations or evaluating of specific chemicals. The object is to evaluate and compare known or newly tried inhibitor test methods for field applications. INTRODUCTION Screening, testing and evaluating of scale inhibitors for oil, gas and geothermal field operations still represents a rather obscure problem area to the industry. The open literature reveals a â??state of anarchyâ?¿ when it comes to scale inhibitor testing and evaluating. Numerous types of laboratory test methods are described without paying much attention to the actual oil and gas fields, thus resulting in numerous sets of irrelevant and misleading information. Even the scale formation by itself, i.e., its proper recognition and handling in the field is still encumbered by numerous problems despite its technical and economical impacts on field operations [1–5]. Any relevant scale inhibitor testing without fully understanding the scale formation in the field does not seem to be reasonable or even possible. Despite the financial losses to the industry due to scale deposits it may come as a surprise that selecting the most appropriate scale inhibitors and their site-specific application methods is still hampered by numerous and obvious problems.
- North America > United States > Texas (1.00)
- Europe (0.93)
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- Asia > Middle East > Iran > Ilam (0.24)
- Water & Waste Management > Water Management > Water & Sanitation Products (1.00)
- Water & Waste Management > Water Management > Constituents > Salts/Sulphates/Scales (1.00)
- Materials > Chemicals > Specialty Chemicals (1.00)
- Energy > Oil & Gas > Upstream (1.00)
...16697 Designing Laboratory Test Protocols for Asphaltenes Deposition Andrew R. Farrell, Benjamin Martin, Dario M. Frigo, & Gordon ... EH54 5DL UK ABSTRACT Asphaltenes deposition is associated with several detrimental effects on oil production, paramount among these being ...production deferment and integrity issues. The current paper presents an investigation of asphaltenes risk ass...
...es (e.g., enhanced emulsion stability, solids fill in separators), these generally occur in surface production facilities and do not result in flow-assurance or integrity problems further upstream. Asphaltenes ...to allow visual observation) rather than those composed of steel, the most-likely material used for production tubing in the field. In this paper we present a new laboratory ...test method that is relatively quick, inexpensive, based on deposition and offers good correlation with ...
...endent on the asphaltenes nature and stability state and are, therefore, specific to each crude and production system, with reported values varying from 1,000 s -1 to 100,000 s -1 . In order to design a... test methodology that allows assessment of asphaltenes deposition risk and evaluation of inhibitor perfo...sing a case study. EXPERIMENTAL PROCEDURE Asphaltenes Dispersancy Tests The asphaltenes dispersancy test (ADT) is one of the most common methods for screening AI, due to its speed, ease and low cost. 5 ...
Abstract Asphaltenes deposition is associated with several detrimental effects on oil production, paramount among these being production deferment and integrity issues. The current paper presents an investigation of asphaltenes risk assessment and mitigation strategies using a dynamic flow test method. It includes a study of the key parameters that influence observation of asphaltenes deposition in the laboratory and how laboratory testing methodologies can be designed to match more closely the processes occurring in the field. In these dynamic tests, dead crude oil is co-injected with n-heptane through a capillary and an inline filter, allowing assessment of both deposition and precipitation in a single test. The method is able to assess deposition tendency and rank asphaltenes inhibitor chemicals under flowing conditions and at more field-representative temperature and pressure, and with much lower volume fractions of n-heptane than required for conventional asphaltenes laboratory tests. Fluid dynamics is recognised to play a key role in the extent of asphaltenes deposition and is often most severe under low-shear conditions because erosive forces can reduce or eliminate deposition at higher shear. Using the dynamic flow test method with capillaries of differing internal diameter, we investigate the factors that either promote or suppress deposition, and determine certain boundary conditions where deposition is inhibited under the influence of increasing shear. The dynamic method is also used to evaluate the effectiveness of asphaltenes inhibitor chemicals against both precipitation and deposition, thus demonstrating that this approach provides much more relevant chemical-performance data than conventional test approaches, and may even elucidate why chemicals selected using non-dynamic methods often perform indifferently in the field or sometimes fail to perform completely. Introduction Background It is estimated that approximately 5 – 10% of the world's crude oils are susceptible to asphaltenes issues, which can cause flow restrictions, compromised integrity including malfunction of control and monitoring equipment, loss of well access for interventions, enhanced emulsion stability and internal under-deposit corrosion. Despite this, currently used methods to assess asphaltenes deposition risk and evaluate the laboratory performance of asphaltenes inhibitors are non-optimal because the conditions used are so far from those prevailing in the field. This can lead to inadequate assessment of risk, erroneous ranking of candidate inhibitors and even selection of chemicals that may not be beneficial in the field at all.
- North America > United States (0.46)
- Asia > Middle East > Israel > Mediterranean Sea (0.24)
...SPE 164334 Well Test Rate Conversion to Compositional Wellstream Mohammad Faizul Hoda, SPE, Petrostreamz AS, Curtis Hay...ot be copied. The abstract must contain conspicuous acknowledgment of SPE copyright. Abstract Well test rates are measured with ...test separators operating at varying pressure and temperature during initial ...
...a period of six to 24 hours. Regulatory bodies often require periodic individual-well testing, with test frequency ranging from monthly to annually - mostly depending on the time variation of gas-oil rati...rrect in-line multi-phase metering rates. Metering corrections are often assumed invariant from one test to the next when forecasting rate behavior and performing daily or monthly well-rate allocation. Se...veral measurement devices are installed on the gas, oil and water outlets of test separators, most importantly those providing volumes of gas, oil and water, including separator tem...
...mbined in some ratio of moles separator gas to wellstream moles ( /) tha t yields the actual test wellstream composition (1 ). T he ch oi ce of is made to e nsure that the sa...me GOR measured in the actual well test is simulated when flashing composition . All flash calculations are made using an appropriate e...tion. Typically we use the most-recent measured or calculated wellstream as the seed feed. The well test molar component rate is found by scaling the computed seed-feed separator gas mole fractions by...
Abstract Well test rates are measured with test separators operating at varying pressure and temperature during initial production tests for a new well and during periodic tests used to monitor well performance and allocate multi-well production separator rates. Converting test separator gas and oil volumetric rates to a common (fixed) set of surface separator conditions is useful to ensure consistent history matching and rate allocation, development of valid inflow performance relations, and correlating well performance changes over time. This paper provides a method to convert reported test rates to a molar compositional wellstream rate. This compositional wellstream will exactly reproduce the reported test rates at the separator conditions prevailing when rates were measured. The compositional wellstream rate can then be re-processed through a fixed set of separator conditions to provide total surface gas and stock-tank oil rates. The requirements for converting test rates to a compositional wellstream include: (1) an appropriate EOS model, (2) an estimate of the wellstream composition – the "seed feed", (3) test separator volumetric rates, and (4) test separator conditions of pressure and temperature. The seed feed is usually the previously-determined wellstream composition from an earlier test. The seed feed is flashed at test separator pressure and temperature, resulting in equilibrium gas and equilibrium oil compositions. These equilibrium compositions are recombined in a ratio that yields exactly the test separator gas-oil ratio with the EOS model, thereby yielding wellstream composition. Properties of the separator phases are used to convert separator volumes to moles and thereby wellstream molar rate. Sometimes a similar conversion is needed for volumetric gas and oil rates resulting from a multi-stage separation process. An important example is conversion of black-oil rates to compositional wellstreams, where the black-oil PVT tables have been generated from a multi-stage separation process. Finally, we discuss the processing of compositional wellstreams through a higher-level (group, field, or asset) process facility that takes into account the total feed composition of the process facility, and how to back-allocate well contributions of total product rates.
...Production and Reserves Monitoring (PARM) System OSEA/88173 Provide a flexible reporting system. In a paper...routine standard and analytical reports based on company or industry standards. Daily and monthly production reports including product balances and allocation, annual reserves reports were historically all... done by hand calculation. Interface to other applications. To provide production, ...
... The final result fulfilled the users' needs. Modules were built for the initial user review and test quickly, without necessarily having all of the "frills" built in. The process of building and im... one case it was found that produced condensate had been allocated to zones twice in each monthly production allocation calculation. This had the effect of incorrectly overstating ...production and incorrectly reducing remaining gas reserves in-place. When the data was loaded in the relatio...
...Production and Reserves Monitoring (PARM) System OSEA/ 88173 Daily Report Liquid Balance Gas Balance Theor...etical Production Outside Operations Reports Operations Remarks Tanker Lifting Monthly Report Theoretical ...Production Production Allocation zone/Well ...
Abstract Huffco Indonesia has developed and installed a computerized database system called PARM System - Production and Reserves Monitoring System. This integrated database handles data that includes reservoir, geological, production, operations and mechanical well data. while the PARM System data are acquired and controlled from many technical and operations disciplines within the it is always input as close to the original source as possible. The PARM System, as an integrated production and reserves data source for Huffco Indonesia, has applications across a wide range of engineering and operations disciplines. Daily production and operations reports, monthly production allocation and product distribution reports, daily drilling reports and summary reports and many other necessary routine reports are. generated by the PARM System. Benefits of analysis of large volumes of data, which were previously very cumbersome to attempt, are now being realized by engineering groups. Ad-hoc data retrievals provide consistent current and historical data for production and reservoir engineering applications. An integrated computerized database system such as the PARM System, provides a cost and time efficient engineering and operations tool. It provides unparalleled accessibility to any data likely to affect or resulting from the oil and gas production of a well, zone or field. Accuracy of original data is improved due to multi-user review and built-in integrity chocks. Development of a system, such as the PARM System, should be done on a prototype basis under direct engineering management. Application of computer technology to the petroleum industry is manifested in the PARM System by virtue of capturing and handling of the basic oil and gas operations and engineering data. This paper describes the design and implementation concepts of the PARM System as well as engineering and operations applications ranging from simple reports and data retrievals to interfacing with reservoir simulation software. Introduction Huffco Indonesia is the operator of an oil and gas Production Sharing Contract (PSC) area in East Kalimantan, Indonesia. Wells in the PSC area currently range to 15,000 feet in depth with producing horizons being completed in various intervals between 1000 feet to 12000 feet. In one of the four currently producing fields, Badak, there are more 200 unique zones. Producing and producing fields have a total of 336 wells. Many of the wells in the producing fields have dual or multiple completions with some having commingled zone production. while the four currently producing fields produce approximately 37000 barrels of oil and condensate per day, the major production is natural gas where the capability is in excess of 1 billion standard cubic feet per day. The natural gas production, after processing at the respective fields, is supplied to the Bontang LNG plant where it is liquefied and utilized to fulfill contracts with offshore buyers. With firm long-term contracts in effect, it is imperative that the supply be able to meet the demand. To insure that this criterion is maintained it is essential to have an accurate, current, accessible database of the various parameters affecting the ability to supply. Huffco, with consulting assistance, performed project definition and planning study which aided in defining objectives and the philosophy of operation of a Production and Reserves monitoring System. In assessing the large volume of interrelated data to be handled the objectives of Production and Reserves Monitoring System were defined to be as follows:–Provide timely common access to basic data for performance monitoring. Under the existing system considerable time could pass before basic data such as well tests, would reach personnel responsible for monitoring and analysing well performance. –Minimize redundancy of information handling, transcribing, summarizing and copying of data resulting in time loss and frequent data transcribing errors. P. 614^
- Asia > Indonesia > East Kalimantan (0.54)
- Asia > Middle East > Israel > Mediterranean Sea (0.24)