Simulation of many enhanced oil recovery (EOR) methods such as water alternative gas (WAG) requires accurate determination of relative permeability (kr) data under different saturation histories. Relative permeability is a function of several factors such as wettability, spreading coefficient and fluid pore occupancy. Experimental measurements of three phase kr data are time consuming and difficult considering infinite possible flow paths in the three-phase flow regime. There are several models in the literature to estimate the oil relative permeability data in three phase systems (3P-Kr models). However, the available models can not accurately estimate the oil production in low oil saturation region observed in WAG experiments. In this paper, Stone I model has been modified to improve the estimation of oil kr data. To this aim, the behaviors of three phase flow in immiscible and near miscible WAG experiments were considered. It was shown that the Stone model overestimates the oil relative permeability data in the low oil saturation regions. In addition, it was revealed that Stone's exponent model cannot simulate the gradual decreace in the oil kr data. To improve the results, a new coefficient is incorporated into the model to consider the impacts of the disconnected oil clusters during the cyclic injection. In addition, the end-of-cycle residual oil saturation (Som), which was required based on the Stone model, is no longer needed in this modified model.
{"title":"Estimation of Three-phase Oil Relative Permeability in WAG Experiments","authors":"S. Aghabozorgi, M. Sohrabi, J. Façanha","doi":"10.4043/29924-ms","DOIUrl":"https://doi.org/10.4043/29924-ms","url":null,"abstract":"\u0000 Simulation of many enhanced oil recovery (EOR) methods such as water alternative gas (WAG) requires accurate determination of relative permeability (kr) data under different saturation histories. Relative permeability is a function of several factors such as wettability, spreading coefficient and fluid pore occupancy. Experimental measurements of three phase kr data are time consuming and difficult considering infinite possible flow paths in the three-phase flow regime. There are several models in the literature to estimate the oil relative permeability data in three phase systems (3P-Kr models). However, the available models can not accurately estimate the oil production in low oil saturation region observed in WAG experiments.\u0000 In this paper, Stone I model has been modified to improve the estimation of oil kr data. To this aim, the behaviors of three phase flow in immiscible and near miscible WAG experiments were considered. It was shown that the Stone model overestimates the oil relative permeability data in the low oil saturation regions. In addition, it was revealed that Stone's exponent model cannot simulate the gradual decreace in the oil kr data. To improve the results, a new coefficient is incorporated into the model to consider the impacts of the disconnected oil clusters during the cyclic injection. In addition, the end-of-cycle residual oil saturation (Som), which was required based on the Stone model, is no longer needed in this modified model.","PeriodicalId":10927,"journal":{"name":"Day 3 Thu, October 31, 2019","volume":"60 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83013818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marco Aurélio Gemaque Cantuaria, Maria Pontes Pedrosa Peczek
The present paper tries to understand how ANP Regulation n.° 03/2015 affected the Research and Development (R&D) in Brazil in the Oil and Gas Industry, by identifying the amount of projects, institutions involved, investment executed, companies responsible, and the whole research landscape along with a thorough analysis of the process and main numbers.
{"title":"Analysis of Brazilian's Oil and Gas Industry Research Fostering","authors":"Marco Aurélio Gemaque Cantuaria, Maria Pontes Pedrosa Peczek","doi":"10.4043/29884-ms","DOIUrl":"https://doi.org/10.4043/29884-ms","url":null,"abstract":"\u0000 The present paper tries to understand how ANP Regulation n.° 03/2015 affected the Research and Development (R&D) in Brazil in the Oil and Gas Industry, by identifying the amount of projects, institutions involved, investment executed, companies responsible, and the whole research landscape along with a thorough analysis of the process and main numbers.","PeriodicalId":10927,"journal":{"name":"Day 3 Thu, October 31, 2019","volume":"86 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74801447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. C. Bravo, E. Nieves, L. Arcaya, D. Magnelli, A. Dabrowski
Tight gas reservoir has potential to provide a significant contribution to meet the global energy demand. Unconventional resource plays and in particular tight gas reservoir are generally characterized by lower geologic risk but higher commercial risk. For that reason, a precise understanding of the potential range can lead to the commercial success; this weighs on the economic evaluation process. The cutting-edge method "Technical Datamining" (DM), use artificial intelligence, statists, and algorithm of learning machines to accomplish new knowledge of clustering and predictive types. Neural networks-DM are computational models that have been used in different research fields with outstanding results. Thus, models of temporal series are pursued to develop to achieve reliable estimations of the main economic indexes: NPV, IRR, Payout and investment performance in the high-risk Oil & Gas portfolios, in particular economic evaluation of unconventional/Tight Gas resources, which is our concern. Neural networks learn from experience and errors: when more wells of the investment's portfolios are added, the experience will improve. The process of knowledge improvement begins with the extraction, transformation and loading data to the collection of the resultant model and its analysis. This involves an exhaustive work with the exploration and evaluation with the behavior of independent variables (Capex, Opex, Reserves, Gas Price and Time), the outliers, the normalization, variability and the distributions. Furthermore, it is vital to maintain a complex and extensive training of the neural network model with different parameters and iterations, using the previous experience's expert. Our study has 4 years and a monthly seasonality for processing the data in the search to optimize decision making. The model application will be developed in the sectoral block of the Lajas Formation of the Neuquén Basin, with six wells in production, the GOIS value above 3000 MMm3 and the current recover factor estimated in 19 %. In addition to this, are expected the incorporation of new wells to the block to increase the recovery factor above 35 % and thus improve the return on investment (NPV / Investment). Finally, the construction of neural network model will provide predictive values more precisely through a time series using 80 % focusing on tasks for training and 20% for testing, with minor errors of 5 %. Extracting hidden knowledge or information not trivial of dataset to be used in making decision. Discovery of unknown models [1][2] in order to discover meaningful patterns and rules [3].
{"title":"Predictive Data Mining Techniques for Economic Evaluation of Unconventional Resources: The Tight Gas of Argentina","authors":"R. C. Bravo, E. Nieves, L. Arcaya, D. Magnelli, A. Dabrowski","doi":"10.2118/185490-MS","DOIUrl":"https://doi.org/10.2118/185490-MS","url":null,"abstract":"\u0000 Tight gas reservoir has potential to provide a significant contribution to meet the global energy demand. Unconventional resource plays and in particular tight gas reservoir are generally characterized by lower geologic risk but higher commercial risk. For that reason, a precise understanding of the potential range can lead to the commercial success; this weighs on the economic evaluation process.\u0000 The cutting-edge method \"Technical Datamining\" (DM), use artificial intelligence, statists, and algorithm of learning machines to accomplish new knowledge of clustering and predictive types. Neural networks-DM are computational models that have been used in different research fields with outstanding results. Thus, models of temporal series are pursued to develop to achieve reliable estimations of the main economic indexes: NPV, IRR, Payout and investment performance in the high-risk Oil & Gas portfolios, in particular economic evaluation of unconventional/Tight Gas resources, which is our concern. Neural networks learn from experience and errors: when more wells of the investment's portfolios are added, the experience will improve.\u0000 The process of knowledge improvement begins with the extraction, transformation and loading data to the collection of the resultant model and its analysis. This involves an exhaustive work with the exploration and evaluation with the behavior of independent variables (Capex, Opex, Reserves, Gas Price and Time), the outliers, the normalization, variability and the distributions. Furthermore, it is vital to maintain a complex and extensive training of the neural network model with different parameters and iterations, using the previous experience's expert. Our study has 4 years and a monthly seasonality for processing the data in the search to optimize decision making.\u0000 The model application will be developed in the sectoral block of the Lajas Formation of the Neuquén Basin, with six wells in production, the GOIS value above 3000 MMm3 and the current recover factor estimated in 19 %. In addition to this, are expected the incorporation of new wells to the block to increase the recovery factor above 35 % and thus improve the return on investment (NPV / Investment). Finally, the construction of neural network model will provide predictive values more precisely through a time series using 80 % focusing on tasks for training and 20% for testing, with minor errors of 5 %.\u0000 Extracting hidden knowledge or information not trivial of dataset to be used in making decision. Discovery of unknown models [1][2] in order to discover meaningful patterns and rules [3].","PeriodicalId":10927,"journal":{"name":"Day 3 Thu, October 31, 2019","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75912266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Catalina Camargo, J. V. Vargas, E. Ruidiaz, A. Winter, E. Koroishi, O. V. Trevisan, R. V. D. Almeida, G. S. Bassani
A new methodology to study naturally fracture reservoir with an induced fracture model was proposed using a representative sample of the Pre-salt reservoir. A core was cut longitudinally while the fracture was simulated using a polyoxymethylene spacer (POM). This fracture configuration was adapted based on the studies performed by Lie (2013) and improved with filling the voids with spheres with controlled grain size to represent a porous medium and increase the permeability and porosity of the fracture. To study the effect of injection of low salinity waterflooding, a forced displacement test was performed under pressure conditions of 1000 psi, temperature of 63°C, and flow rate of 0.1 ml/min. The core sample was prepared at initial water saturation (Swi). This process was carried out by forced displacement and a vacuum procedure in the coreholder using synthetic formation water and dead oil of the same field as the core. The sample was aged for 34 days to simulate the wettability reservoir conditions. During the test, the syntethic seawater (SW) injection was started, and, after eight days, it was switched to ten times diluted seawater (SW10x) for 22 days. Oil production was calculated by mass balance. The X-ray computed tomography (CT) technique was used to evaluate the heterogeneity of the porosity distribution and the saturations at different injection times during the Swi process. To validate the petrophysical properties, it was performed a systematic routine for the determination of the petrophysical properties of the induced fracture model and its components: matrices and fracture. The porosity and permeability for the matrices were 11% and 31 mD for part A and are 10% and 22 mD for part B. respectively. The porosity of the fracture was analytically calculated resulting in 1.6% while the permeability of the fracture was adjusted according to the theory of flow in parallel layers resulting in 129 D. Finally, the induced fractured rock showed a porosity and permeability of 21% and 3.6 D, respectively. The Swi reached 32% and 33% by using mass balance and computed tomography (CT), respectively. Additionally, CT scans provided the Swi profiles throughtout the sample. The results of production have shown that oil recovery with injection SW was 20.8% original oil in place (OOIP) and additional recovery from the injection of SW10X of 17.33%OOIP while the final recovery was around 38.13%OOIP.
{"title":"Study of the Effect of Low Salinity Water Injection on the Oil Recovery Factor in Fractured Carbonate Rocks Using Computed Tomography","authors":"Catalina Camargo, J. V. Vargas, E. Ruidiaz, A. Winter, E. Koroishi, O. V. Trevisan, R. V. D. Almeida, G. S. Bassani","doi":"10.4043/29939-ms","DOIUrl":"https://doi.org/10.4043/29939-ms","url":null,"abstract":"\u0000 A new methodology to study naturally fracture reservoir with an induced fracture model was proposed using a representative sample of the Pre-salt reservoir. A core was cut longitudinally while the fracture was simulated using a polyoxymethylene spacer (POM). This fracture configuration was adapted based on the studies performed by Lie (2013) and improved with filling the voids with spheres with controlled grain size to represent a porous medium and increase the permeability and porosity of the fracture. To study the effect of injection of low salinity waterflooding, a forced displacement test was performed under pressure conditions of 1000 psi, temperature of 63°C, and flow rate of 0.1 ml/min. The core sample was prepared at initial water saturation (Swi). This process was carried out by forced displacement and a vacuum procedure in the coreholder using synthetic formation water and dead oil of the same field as the core. The sample was aged for 34 days to simulate the wettability reservoir conditions. During the test, the syntethic seawater (SW) injection was started, and, after eight days, it was switched to ten times diluted seawater (SW10x) for 22 days. Oil production was calculated by mass balance. The X-ray computed tomography (CT) technique was used to evaluate the heterogeneity of the porosity distribution and the saturations at different injection times during the Swi process. To validate the petrophysical properties, it was performed a systematic routine for the determination of the petrophysical properties of the induced fracture model and its components: matrices and fracture. The porosity and permeability for the matrices were 11% and 31 mD for part A and are 10% and 22 mD for part B. respectively. The porosity of the fracture was analytically calculated resulting in 1.6% while the permeability of the fracture was adjusted according to the theory of flow in parallel layers resulting in 129 D. Finally, the induced fractured rock showed a porosity and permeability of 21% and 3.6 D, respectively. The Swi reached 32% and 33% by using mass balance and computed tomography (CT), respectively. Additionally, CT scans provided the Swi profiles throughtout the sample. The results of production have shown that oil recovery with injection SW was 20.8% original oil in place (OOIP) and additional recovery from the injection of SW10X of 17.33%OOIP while the final recovery was around 38.13%OOIP.","PeriodicalId":10927,"journal":{"name":"Day 3 Thu, October 31, 2019","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72772253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As part of any Source Control Emergency Response Plan (SCERP), capping a subsea well blowout is a significant contingency operation that requires attention to many details to ensure that an operator is prepared to manage the risks involved and to achieve the desired outcome of stopping the flow of an uncontrolled well. The objective of this paper is to identify and describe the technical considerations (the science behind the procedures) that a prudent operator must address to be able to efficiently and effectively store, maintain, mobilize, install and operate a subsea capping stack in a subsea well blowout event. The paper will offer a brief description of the critical design and functionality requirements that were considered in the development of the original capping stacks. It will contain some updated guidance regarding storage, maintenance and transportation of a capping stack to the incident site. This paper will also present the latest review of available installation methods and offer a brief narrative regarding operating procedures. The paper will also briefly relay portions of the newly-released guidelines introduced in IOGP Report 594, dated January 2019, regarding the need for and definition of an effective SCERP. It has been almost 10 years since the last catastrophic offshore well control incident and the industry has responded by building equipment and developing procedures to enable an effective response to a similar incident. However, operating in an offshore environment requires a perpetual risk assessment and constant review and evaluation of contingency plans for all procedures, especially for those relating to protecting the environment. This paper will present an operator with proven guidance statements to enable the operator to properly prepare for a subsea well control incident. This paper will present updated guidance regarding selected technical issues of capping stack design and pertinent updated guidance regarding capping stack storage, maintenance, mobilization, and installation. The paper will also reinforce the newly released SCERP guidance regarding capping stacks in IOGP Report 594, dated January 2019.
{"title":"The Science of Capping a Subsea Well Blowout","authors":"Mitch Guinn, Mike Cargol","doi":"10.4043/29926-ms","DOIUrl":"https://doi.org/10.4043/29926-ms","url":null,"abstract":"\u0000 As part of any Source Control Emergency Response Plan (SCERP), capping a subsea well blowout is a significant contingency operation that requires attention to many details to ensure that an operator is prepared to manage the risks involved and to achieve the desired outcome of stopping the flow of an uncontrolled well.\u0000 The objective of this paper is to identify and describe the technical considerations (the science behind the procedures) that a prudent operator must address to be able to efficiently and effectively store, maintain, mobilize, install and operate a subsea capping stack in a subsea well blowout event.\u0000 The paper will offer a brief description of the critical design and functionality requirements that were considered in the development of the original capping stacks. It will contain some updated guidance regarding storage, maintenance and transportation of a capping stack to the incident site. This paper will also present the latest review of available installation methods and offer a brief narrative regarding operating procedures. The paper will also briefly relay portions of the newly-released guidelines introduced in IOGP Report 594, dated January 2019, regarding the need for and definition of an effective SCERP.\u0000 It has been almost 10 years since the last catastrophic offshore well control incident and the industry has responded by building equipment and developing procedures to enable an effective response to a similar incident. However, operating in an offshore environment requires a perpetual risk assessment and constant review and evaluation of contingency plans for all procedures, especially for those relating to protecting the environment. This paper will present an operator with proven guidance statements to enable the operator to properly prepare for a subsea well control incident.\u0000 This paper will present updated guidance regarding selected technical issues of capping stack design and pertinent updated guidance regarding capping stack storage, maintenance, mobilization, and installation. The paper will also reinforce the newly released SCERP guidance regarding capping stacks in IOGP Report 594, dated January 2019.","PeriodicalId":10927,"journal":{"name":"Day 3 Thu, October 31, 2019","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79654254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Punase, Claudia Mazzeo, R. Garan, E. Vita, Ryan Kristensen, J. Wylde
Asphaltene precipitation and deposition is a major flow assurance issue faced by the oil and gas industry. The complex nature and non-uniform molecular structure of asphaltenes complicates efforts to accurately assess their stability. Moreover, developing test methodologies with strong laboratory-to-field correlation presents additional challenges. The focus of this study is to discuss the successful validation and application of a novel test method for determination and monitoring of asphaltene stability in a Gulf of Mexico deepwater field. Remediation and stimulation procedures were performed on a deep-water field in the Gulf of Mexico experiencing severe asphaltene deposition problems in the wellbore and near-wellbore region. This study evaluates the correlation between the thermo-electric properties as determined by Asphaltene Differential Aggregation Probe Testing (ADAPT) and dispersion tendencies of asphaltenes in treated and untreated crude oil samples at both laboratory and field environments. The remediation job was conducted through a multi-step process involving a coiled tubing clean out, solvent-soak, and continuous AI injection through downhole chemical injection tubing following the stimulation. Samples were collected prior to the start of treatment, during the initial flow-back of stimulation fluids, and over the course of one year following the stimulation. Field ADAPT measurements were performed to monitor the effect of continuous Asphaltene Inhibitor (AI) injection over time and validate the direct laboratory-to-field relationship. Higher ADAPT readings are indicative of a better dispersion state of the polar asphaltene fraction within the test sample. Hence, the pre-treatment samples were observed to have lower ADAPT values as compared to the flow-back samples collected after the solvent-soak stage. Stabilized higher readings were recorded for the samples analyzed in the next three months and a step-down trend was observed with reduction in AI dosage. Additionally, the amount of asphaltenes that precipitated from the field samples were also measured and followed an inverse relationship with the ADAPT values, corroborating the expected asphaltene stability behavior. Furthermore, differential pressure across the flowline was also monitored for this well to confirm the absence of asphaltene deposition throughout the assessment period. A strong correlation between the laboratory and field results obtained from this thermo-electric technique and its validation with other industry standard methods highlight the reliability and high degree of accuracy of the novel ADAPT method. With this study, an innovative method of assessing and monitoring the stability of asphaltenes and efficiency of an AI within the native crude oil medium is presented. The effectiveness of the technique to decipher and record variations during different stages of an asphaltene remediation job demonstrates its robustness and applicability as an efficient mo
{"title":"Novel in-Field Technique to Monitor and Optimize Asphaltene Remediation and Inhibition Job with Direct Field-to-Laboratory Correlation","authors":"A. Punase, Claudia Mazzeo, R. Garan, E. Vita, Ryan Kristensen, J. Wylde","doi":"10.4043/29887-ms","DOIUrl":"https://doi.org/10.4043/29887-ms","url":null,"abstract":"\u0000 Asphaltene precipitation and deposition is a major flow assurance issue faced by the oil and gas industry. The complex nature and non-uniform molecular structure of asphaltenes complicates efforts to accurately assess their stability. Moreover, developing test methodologies with strong laboratory-to-field correlation presents additional challenges. The focus of this study is to discuss the successful validation and application of a novel test method for determination and monitoring of asphaltene stability in a Gulf of Mexico deepwater field.\u0000 Remediation and stimulation procedures were performed on a deep-water field in the Gulf of Mexico experiencing severe asphaltene deposition problems in the wellbore and near-wellbore region. This study evaluates the correlation between the thermo-electric properties as determined by Asphaltene Differential Aggregation Probe Testing (ADAPT) and dispersion tendencies of asphaltenes in treated and untreated crude oil samples at both laboratory and field environments. The remediation job was conducted through a multi-step process involving a coiled tubing clean out, solvent-soak, and continuous AI injection through downhole chemical injection tubing following the stimulation. Samples were collected prior to the start of treatment, during the initial flow-back of stimulation fluids, and over the course of one year following the stimulation. Field ADAPT measurements were performed to monitor the effect of continuous Asphaltene Inhibitor (AI) injection over time and validate the direct laboratory-to-field relationship.\u0000 Higher ADAPT readings are indicative of a better dispersion state of the polar asphaltene fraction within the test sample. Hence, the pre-treatment samples were observed to have lower ADAPT values as compared to the flow-back samples collected after the solvent-soak stage. Stabilized higher readings were recorded for the samples analyzed in the next three months and a step-down trend was observed with reduction in AI dosage. Additionally, the amount of asphaltenes that precipitated from the field samples were also measured and followed an inverse relationship with the ADAPT values, corroborating the expected asphaltene stability behavior. Furthermore, differential pressure across the flowline was also monitored for this well to confirm the absence of asphaltene deposition throughout the assessment period. A strong correlation between the laboratory and field results obtained from this thermo-electric technique and its validation with other industry standard methods highlight the reliability and high degree of accuracy of the novel ADAPT method.\u0000 With this study, an innovative method of assessing and monitoring the stability of asphaltenes and efficiency of an AI within the native crude oil medium is presented. The effectiveness of the technique to decipher and record variations during different stages of an asphaltene remediation job demonstrates its robustness and applicability as an efficient mo","PeriodicalId":10927,"journal":{"name":"Day 3 Thu, October 31, 2019","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78797291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Along the enhancement of data processing and storing capabilities, introduction of cloud computing and a broader connectivity between different systems, data mining techniques and machine learning consolidate themselves between the main exponents for business improvement. Even areas of industry considerably mature, as the oil & gas, shall handle these tools to modernize its processes and enhance their efficiency. The applicable fields are diverse, from the operational realm to management areas. It is remarkable to consider the benefits that the adoption of richer prediction models would provide, in substitution of tasks so far performed only from empiricism, or under minimal premises. Towards planning, data mining associated with machine learning turns into an important tool for some services demand prediction. Especially those at which the occurrence is essentially probabilistic. Such analysis may be implemented crossing multiple input data, allowing the model to be a fair representation of reality. Fishing occurrence is an unmistakable example of well service with probabilistic incidence. Even if, at a first glance, their manifestation seems chaotic, fishing incidence varies according the activities performed or well specifications. This means the event probability depends not only if the rig is drilling or completing, but also on well specification. In a large oil company, with a large amount of wells, the possibility of a multi-variable prediction for this kind of occurrence is very valuable for a proper mapping and dimensioning of the service amount. This present paper shows the steps of quantifying the demand for fishing services using previous experience. These steps are explained, from input data classification and pre-processing through the choice of the fittest machine learning model, and finally, the process and analysis of the obtained results. Once the model is defined and implemented, each new analysis can be performed quickly. This represents a massive time saving, especially when schedule changes happen very often. However, the advantages obtained are not only restricted to the boost in performance, but also the possibility to consider a larger assortment of input variables, and therefore allow the user to obtain a model closer to reality, and still capable of be continuously improved and adapted to new scenarios. Regardless being the purpose of this work the amount of services to hire, the obtained data are also a great source for fishing prevention, aiming to reduce nonproductive time (NPT). It can provide an intensity map, indicating the activities at which shall the efforts be prioritized. They are still useful in rig schedule forecasting, to permit predicting the amount of time for each activity regarding fishing events. Finally, regardless of referring to fishing activity, the methods and process used in this work may be, in general, used for other purposes, within or outside the oil industry.
{"title":"Machine Learning Applied on Fishing Occurrence Prediction","authors":"Flavio Tito Peixoto Filho, Juarez Guaraci Filardo","doi":"10.4043/29700-ms","DOIUrl":"https://doi.org/10.4043/29700-ms","url":null,"abstract":"\u0000 Along the enhancement of data processing and storing capabilities, introduction of cloud computing and a broader connectivity between different systems, data mining techniques and machine learning consolidate themselves between the main exponents for business improvement. Even areas of industry considerably mature, as the oil & gas, shall handle these tools to modernize its processes and enhance their efficiency. The applicable fields are diverse, from the operational realm to management areas. It is remarkable to consider the benefits that the adoption of richer prediction models would provide, in substitution of tasks so far performed only from empiricism, or under minimal premises. Towards planning, data mining associated with machine learning turns into an important tool for some services demand prediction. Especially those at which the occurrence is essentially probabilistic. Such analysis may be implemented crossing multiple input data, allowing the model to be a fair representation of reality. Fishing occurrence is an unmistakable example of well service with probabilistic incidence. Even if, at a first glance, their manifestation seems chaotic, fishing incidence varies according the activities performed or well specifications. This means the event probability depends not only if the rig is drilling or completing, but also on well specification. In a large oil company, with a large amount of wells, the possibility of a multi-variable prediction for this kind of occurrence is very valuable for a proper mapping and dimensioning of the service amount.\u0000 This present paper shows the steps of quantifying the demand for fishing services using previous experience. These steps are explained, from input data classification and pre-processing through the choice of the fittest machine learning model, and finally, the process and analysis of the obtained results.\u0000 Once the model is defined and implemented, each new analysis can be performed quickly. This represents a massive time saving, especially when schedule changes happen very often. However, the advantages obtained are not only restricted to the boost in performance, but also the possibility to consider a larger assortment of input variables, and therefore allow the user to obtain a model closer to reality, and still capable of be continuously improved and adapted to new scenarios.\u0000 Regardless being the purpose of this work the amount of services to hire, the obtained data are also a great source for fishing prevention, aiming to reduce nonproductive time (NPT). It can provide an intensity map, indicating the activities at which shall the efforts be prioritized. They are still useful in rig schedule forecasting, to permit predicting the amount of time for each activity regarding fishing events. Finally, regardless of referring to fishing activity, the methods and process used in this work may be, in general, used for other purposes, within or outside the oil industry.","PeriodicalId":10927,"journal":{"name":"Day 3 Thu, October 31, 2019","volume":"58 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85333371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mechanically lined pipe (MLP) has been successfully used in many applications where the fatigue load is low. The use of mechanically lined pipe in higher fatigue load applications require proof of fatigue strength and therefore, additional testing, including full scale fatigue testing, are typically performed. Petrobras has been a pioneer in this work and has developed an MLP specification designating in detail the qualification conditions for using MLP pipe in dynamic applications (see [1]). This paper describes the qualification of Cladtek MLP for dynamic applications including the results of full-scale fatigue testing and a concept, designed by Cladtek, intended to further improve fatigue performance of MLP. Cladtek has filed a patent application for this concept named: Upset-end MLP with improved fatigue resistance [3]. This document presents full-scale fatigue testing results higher than experimental data previously available but in line with the results presented by Subsea 7 in the document IBP1137_15 (see [4]). These results demonstrate that improved fabrication techniques could lead to the use of MLP in the applications with high fatigue demand where, up to now, only clad pipes were considered suitable for use. The use of MLP in high fatigue load applications results in substantial cost savings.
{"title":"Mechanically Lined Pipe MLP with Improved Fatigue Resistance","authors":"S. Popescu, P. Montague","doi":"10.4043/29768-ms","DOIUrl":"https://doi.org/10.4043/29768-ms","url":null,"abstract":"\u0000 Mechanically lined pipe (MLP) has been successfully used in many applications where the fatigue load is low. The use of mechanically lined pipe in higher fatigue load applications require proof of fatigue strength and therefore, additional testing, including full scale fatigue testing, are typically performed. Petrobras has been a pioneer in this work and has developed an MLP specification designating in detail the qualification conditions for using MLP pipe in dynamic applications (see [1]).\u0000 This paper describes the qualification of Cladtek MLP for dynamic applications including the results of full-scale fatigue testing and a concept, designed by Cladtek, intended to further improve fatigue performance of MLP. Cladtek has filed a patent application for this concept named: Upset-end MLP with improved fatigue resistance [3].\u0000 This document presents full-scale fatigue testing results higher than experimental data previously available but in line with the results presented by Subsea 7 in the document IBP1137_15 (see [4]). These results demonstrate that improved fabrication techniques could lead to the use of MLP in the applications with high fatigue demand where, up to now, only clad pipes were considered suitable for use. The use of MLP in high fatigue load applications results in substantial cost savings.","PeriodicalId":10927,"journal":{"name":"Day 3 Thu, October 31, 2019","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89971116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Souza, F. Pessoa, T. Ferreira, E. Calixto, A. L. C. Bonfim
Hydrogen sulfide (H2S), usually present in oil reservoirs, is a toxic and corrosive gas that may have its origin associated with bacteria's metabolism or thermochemical reactions. This gas which is already present in the atmosphere can be converted into sulfur dioxide (SO2), contributing to the greenhouse effect. In presence of water it forms sulfuric acid and precipitates as acid rain. Given its physicochemical properties, H2S tends to accumulate in spaces with little ventilation; being a serious condition in operational processes. Even in low concentrations it causes health problems, and itis lethal in concentrations close to 700 ppm. Nevertheless, the corrosive potential must also be considered, mainly during production due to the piping can be affected with leaks. Therefore, the treatment should still be effective close to the reservoir during the oil production process. These problems must be overcome by the effective reduction or removal of this gas from the oil stream. The use of H2S scavengers in oil industry is a useful practice in order to remove or reduce gas concentration. Hydrogen sulfide scavengers based on triazines are used, since they are liquid substances that can be used in gas systems, being able to be injected directly into the stream with great mixing capacity. The triazine reacts with H2S producing soluble and inert products, which are collected during production system. In order to monitoring H2S concentration, a software SIMSeq 1.0 was used to simulate operational conditions based on real data from oil wells. Using this software, several simulations were carried out and the optimum injection volume was determined. After the volume set, sensitivities analysis was carried out for different injection depths of scavengers along the well string. The results allowed to draw the best correlation between triazine flowrate and its injection depth. It was done by comparing the scavenger injection depth along the points of injection into wellbore. These results were used to build a predictive model in STATISTICA software with a distribution between volume of injection and sequestration efficiency to support economic feasibility studies for fields and oil wells. Results from this study lead us to believe that for the well studied, considering simulations e statistical analysis performed, the optimum injection depth and flowrate to have H2S concentrations below 5 ppm should be 9500 m for depth and 46 L/h flow rate.
{"title":"Optimization Algorithm of Hydrogen Sulfide Scavenging Process in Oil Production Industry","authors":"F. Souza, F. Pessoa, T. Ferreira, E. Calixto, A. L. C. Bonfim","doi":"10.4043/29812-ms","DOIUrl":"https://doi.org/10.4043/29812-ms","url":null,"abstract":"\u0000 Hydrogen sulfide (H2S), usually present in oil reservoirs, is a toxic and corrosive gas that may have its origin associated with bacteria's metabolism or thermochemical reactions. This gas which is already present in the atmosphere can be converted into sulfur dioxide (SO2), contributing to the greenhouse effect. In presence of water it forms sulfuric acid and precipitates as acid rain. Given its physicochemical properties, H2S tends to accumulate in spaces with little ventilation; being a serious condition in operational processes. Even in low concentrations it causes health problems, and itis lethal in concentrations close to 700 ppm. Nevertheless, the corrosive potential must also be considered, mainly during production due to the piping can be affected with leaks. Therefore, the treatment should still be effective close to the reservoir during the oil production process. These problems must be overcome by the effective reduction or removal of this gas from the oil stream. The use of H2S scavengers in oil industry is a useful practice in order to remove or reduce gas concentration. Hydrogen sulfide scavengers based on triazines are used, since they are liquid substances that can be used in gas systems, being able to be injected directly into the stream with great mixing capacity. The triazine reacts with H2S producing soluble and inert products, which are collected during production system. In order to monitoring H2S concentration, a software SIMSeq 1.0 was used to simulate operational conditions based on real data from oil wells. Using this software, several simulations were carried out and the optimum injection volume was determined. After the volume set, sensitivities analysis was carried out for different injection depths of scavengers along the well string. The results allowed to draw the best correlation between triazine flowrate and its injection depth. It was done by comparing the scavenger injection depth along the points of injection into wellbore. These results were used to build a predictive model in STATISTICA software with a distribution between volume of injection and sequestration efficiency to support economic feasibility studies for fields and oil wells. Results from this study lead us to believe that for the well studied, considering simulations e statistical analysis performed, the optimum injection depth and flowrate to have H2S concentrations below 5 ppm should be 9500 m for depth and 46 L/h flow rate.","PeriodicalId":10927,"journal":{"name":"Day 3 Thu, October 31, 2019","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89534912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many basins throughout the world are experiencing decline in hydrocarbon production with fields maturing and approaching abandonment. Growth in production is coming either from unconventional reservoirs or from relatively immature and emerging basins. As fields (or clusters of fields) approach abandonment, several issues need consideration. There are several ways in which production decline can be mitigated including: infield drilling, workovers, optimised reservoir & facility management, field rejuvenation. Cost management, increased production and operational improvement are some of the strategies employed to maintain profitable operations. Abandonment of a platform with a large number of wells can be a lengthy process with production continuing throughout that process. As production declines, revenues will eventually no longer cover costs. Within the Petroleum Resources Management System (PRMS), Reserves are limited by "the earliest truncation of either technical, license, or economic limit". If there are no technical or licence restrictions, the economic limit, defined as the the time when the maximum cumulative net cash flow occurs for a project, defines the date up to which Reserves may be booked. Several issues related to the determination of the economic limit by an Economic Limit Test (ELT) in late field life will be discussed. Short periods of negative cash flow may be accommodated, and therefore qualify as Reserves, under certain circumstances provided that the longer term cumulative net cash flow forecast shows that the following positive periods more than offset the negative. The use of maximum cumulative cash flow as the basis for the ELT means that incremental projects with negative cash flow are not included as Reserves. However, once the costs are sunk and a forward-looking assessment is performed, the cash flow is once again positive and Reserves can be assigned. Volumes being produced beyond the economic limit, accompanied by a negative cash flow, should not be classified as Reserves as they are not economic to produce. The assumption within the PRMS is that this is point at which a project will cease production. In some PSC environments, there may be little incentive for operators to make long term investments close to PSC expiry. Even after fields reach their economic limit, they may be reactivated e.g.by infill drilling, IOR, EOR. This may be done by different operators, including National Oil Companies or service companies and/or under different commercial arrangements. However, in practice, there may be several reasons why fields continue to produce when production is sub-economic. Management of Reserves in mature fields is important for many reasons including: providing a financing base for the operator, signalling investment opportunities for field re-activation, improved recovery methods or to justify licence extension. This paper will outline some of the challenges involved in late life field management and how it
{"title":"Management of Reserves in Mature Oil and Gas Fields","authors":"D. Peacock, Andrew Duncan","doi":"10.2118/196252-ms","DOIUrl":"https://doi.org/10.2118/196252-ms","url":null,"abstract":"\u0000 Many basins throughout the world are experiencing decline in hydrocarbon production with fields maturing and approaching abandonment. Growth in production is coming either from unconventional reservoirs or from relatively immature and emerging basins. As fields (or clusters of fields) approach abandonment, several issues need consideration. There are several ways in which production decline can be mitigated including: infield drilling, workovers, optimised reservoir & facility management, field rejuvenation. Cost management, increased production and operational improvement are some of the strategies employed to maintain profitable operations.\u0000 Abandonment of a platform with a large number of wells can be a lengthy process with production continuing throughout that process. As production declines, revenues will eventually no longer cover costs. Within the Petroleum Resources Management System (PRMS), Reserves are limited by \"the earliest truncation of either technical, license, or economic limit\". If there are no technical or licence restrictions, the economic limit, defined as the the time when the maximum cumulative net cash flow occurs for a project, defines the date up to which Reserves may be booked.\u0000 Several issues related to the determination of the economic limit by an Economic Limit Test (ELT) in late field life will be discussed. Short periods of negative cash flow may be accommodated, and therefore qualify as Reserves, under certain circumstances provided that the longer term cumulative net cash flow forecast shows that the following positive periods more than offset the negative. The use of maximum cumulative cash flow as the basis for the ELT means that incremental projects with negative cash flow are not included as Reserves. However, once the costs are sunk and a forward-looking assessment is performed, the cash flow is once again positive and Reserves can be assigned. Volumes being produced beyond the economic limit, accompanied by a negative cash flow, should not be classified as Reserves as they are not economic to produce. The assumption within the PRMS is that this is point at which a project will cease production.\u0000 In some PSC environments, there may be little incentive for operators to make long term investments close to PSC expiry. Even after fields reach their economic limit, they may be reactivated e.g.by infill drilling, IOR, EOR. This may be done by different operators, including National Oil Companies or service companies and/or under different commercial arrangements. However, in practice, there may be several reasons why fields continue to produce when production is sub-economic. Management of Reserves in mature fields is important for many reasons including: providing a financing base for the operator, signalling investment opportunities for field re-activation, improved recovery methods or to justify licence extension. This paper will outline some of the challenges involved in late life field management and how it","PeriodicalId":10927,"journal":{"name":"Day 3 Thu, October 31, 2019","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81299153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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