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Collaborating Authors
Target Field
ABSTRACT Seismic processing often involves suppressing multiples that are an inherent component of collected seismic data. Elaborate multiple prediction and subtraction schemes such as surface-related multiple removal have become standard in industry workflows. In cases of limited spatial sampling, low signal-to-noise ratio, or conservative subtraction of the predicted multiples, the processed data frequently suffer from residual multiples. To tackle these artifacts in the postmigration domain, practitioners often rely on Radon transform-based algorithms. However, such traditional approaches are both time-consuming and parameter dependent, making them relatively complex. In this work, we present a deep learning-based alternative that provides competitive results, while reducing the complexity of its usage, and, hence simplifying its applicability. Our proposed model demonstrates excellent performance when applied to complex field data, despite it being exclusively trained on synthetic data. Furthermore, extensive experiments show that our method can preserve the inherent characteristics of the data, avoiding undesired oversmoothed results, while removing the multiples from seismic offset or angle gathers. Finally, we conduct an in-depth analysis of the model, where we pinpoint the effects of the main hyperparameters on real data inference, and we probabilistically assess its performance from a Bayesian perspective. In this study, we put particular emphasis on helping the user reveal the inner workings of the neural network and attempt to unbox the model.
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (0.46)
- North America > United States > Montana > Target Field (0.99)
- Europe > Norway > North Sea > Central North Sea > South Viking Graben > PL 046 > Block 15/9 > Volve Field > Shetland Group > Åsgard Formation (0.99)
- Europe > Norway > North Sea > Central North Sea > South Viking Graben > PL 046 > Block 15/9 > Volve Field > Shetland Group > Svarte Formation (0.99)
- (18 more...)
ABSTRACT Seismic processing often involves suppressing multiples that are an inherent component of collected seismic data. Elaborate multiple prediction and subtraction schemes such as surface-related multiple removal have become standard in industry workflows. In cases of limited spatial sampling, low signal-to-noise ratio, or conservative subtraction of the predicted multiples, the processed data frequently suffer from residual multiples. To tackle these artifacts in the postmigration domain, practitioners often rely on Radon transform-based algorithms. However, such traditional approaches are both time-consuming and parameter dependent, making them relatively complex. In this work, we present a deep learning-based alternative that provides competitive results, while reducing the complexity of its usage, and, hence simplifying its applicability. Our proposed model demonstrates excellent performance when applied to complex field data, despite it being exclusively trained on synthetic data. Furthermore, extensive experiments show that our method can preserve the inherent characteristics of the data, avoiding undesired oversmoothed results, while removing the multiples from seismic offset or angle gathers. Finally, we conduct an in-depth analysis of the model, where we pinpoint the effects of the main hyperparameters on real data inference, and we probabilistically assess its performance from a Bayesian perspective. In this study, we put particular emphasis on helping the user reveal the inner workings of the neural network and attempt to unbox the model.
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (0.46)
- North America > United States > Montana > Target Field (0.99)
- Europe > Norway > North Sea > Central North Sea > South Viking Graben > PL 046 > Block 15/9 > Volve Field > Shetland Group > Åsgard Formation (0.99)
- Europe > Norway > North Sea > Central North Sea > South Viking Graben > PL 046 > Block 15/9 > Volve Field > Shetland Group > Svarte Formation (0.99)
- (18 more...)
Successful Implementation of a Novel Low-Viscosity Retarded Acid System in a Depleted Reservoir – Case History from Mexico
Lugo, Ramiro (Halliburton, Villahermosa, Tabasco, Mexico) | Guillot, Guillermo (PEMEX, Villahermosa, Tabasco, Mexico) | Mercado, Modesto (PEMEX, Villahermosa, Tabasco, Mexico) | Vasquez, Julio (Hallburton, Houston,Texas) | Colon, Alberto (Halliburton, Villahermosa, Tabasco, Mexico)
Abstract This paper describes the planning and execution of a challenging well stimulation operation on a well in the southeast Mexico basin. The job was successfully executed despite complex conditions and the involvement of multiple services, including Coiled Tubing (CT), downhole tools, and fluid services used in efforts to solve a limited wellbore–reservoir communication. The stimulation design included first-time operator implementation of a chemically retarded acid system proving that depth of penetration can be maximized in an open hole long interval carbonate reservoir using a Hydrochloric Acid (HCl) blend with low viscosity and a nonpolymeric water soluble modifying agent. 1 ½ in CT with a milling tool was used initially in an attempt to overcome mechanical resistance while re-entering the well completion. Subsequent trials to spot and inject fluids with the CT resulted in some success from the first acidizing treatments. The main challenge included designing and implementing a customized matrix acidizing intervention to limit the Near-Wellbore (NWB) spending and opening a pathway in a slotted liner completion with a severe mechanical obstruction. Placement of the reactive stimulation fluids required the application of proper techniques to reduce initial pumping pressure and establishing communication into a carbonate formation. Despite bottom-hole conditions restricting reservoir injection, a comprehensive analysis and operational preparation played a major role in successfully executing this acidizing intervention. Stimulation resulted in a five-fold production increase with a stable post-stimulation wellhead pressure indicating improved wellbore-reservoir communication. Results demonstrated significant advantages to acid stimulation jobs that include chemically retarded HCl without gelling agents or emulsifiers. These improvements include: (a) reduced risks associated with formation damage or HSE concerns if applying only gelled or diesel emulsified acids blends; (b) deployability in high treating pressure wells where pipe friction losses are a major consideration; and (c) achieving maximum acid retardation and deep penetration. This achievement highlights the potential of conducting successful stimulation jobs where an acidizing solution may not normally be the first option in wells with challenging downhole environments restricted to flow.
- North America > Mexico (1.00)
- North America > United States > Texas (0.47)
Development of Emulsified Acid System using Organoclays
Mahmoud, Ali Adel (King Fahd University of Petroleum and Minerals) | AL-Dogail, Ala Shafeq (King Fahd University of Petroleum and Minerals) | Gajbhiye, Rahul Narayanrao (King Fahd University of Petroleum and Minerals) | AlSultan, Abdullah Saad (King Fahd University of Petroleum and Minerals)
Abstract Matrix acidizing technique is used to enhance the production of hydrocarbons from a reservoir, especially in low permeable reservoirs and in the case of formation damage. In carbonate reservoirs, acid stimulation jobs are challenging due to the acid's strong reactivity with the formation. Thus, the ability to create wormholes will be limited. Wormholes allow hydrocarbons to be produced by flowing into the wellbore. Emulsified acids system helps to overcome this challenge by reducing face dissolution. Recently, Pickering emulsions have attracted attention due to their easy preparation and enhanced stability features. In Pickering emulsions, solid microparticles that localize at the interface between liquids are used as stabilizers instead of surfactants. The preparation of emulsified acid system (EAS) is a complex process sensitive to several parameters governing the properties/feature of the emulsified system. The parameter includes mixing the aqueous and oleic phase, the rotational speed, the time of mixing, and the quantity of emulsifying agent (organology). It requires performing several experiments to identify the proper procedure and optimum range of the parameters affecting the emulsified acid preparation of desired properties. In this study, several experiments were performed using three types of organoclays (OC) namely Claytone-SF (strong), Claytone-EM (medium), and Laponite-EP (weak). Thermal stability tests were carried out at room temperature, 80ºC, and 120ºC. Rheology tests were performed for the most stable emulsions. This study investigated the potential of using special nanoparticles as emulsion stabilizers instead of surfactants. A proper sequence of the component mixing and optimum range of the factors affecting the emulsion preparation and properties were identified. This work aims to study the parameters involved in the emulsified acid preparation and optimize them to obtain a stable EAS.
- Well Drilling > Drilling Fluids and Materials > Drilling fluid selection and formulation (chemistry, properties) (1.00)
- Well Completion > Acidizing (1.00)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Carbonate reservoirs (1.00)
- Production and Well Operations > Production Chemistry, Metallurgy and Biology > Downhole chemical treatments and fluid compatibility (1.00)
A Novel Engineered Drilling Solution using a Sourceless Geosteering Bottomhole Assembly to Deliver the Longest Extended-Reach Well in a Carbonate Reservoir, Onshore Abu Dhabi, UAE
Fares, Wael (Halliburton) | Dutta, Ashim (ADNOC Onshore) | Reddy, Rathnakar (ADNOC Onshore) | Baslaib, Moahmed (ADNOC Onshore) | El Shahat, Ayman (ADNOC Onshore) | Cardozo, Luis Gerardo (ADNOC Onshore) | Abdel Meguid, Mohamed (ADNOC Onshore) | Nasrallah, Mena (Halliburton) | Mubeen, Muhammad (Halliburton) | Aki, Ahmet (Halliburton)
Abstract To develop a mature onshore carbonate field in Abu Dhabi and reduce the footprint and cost, an artificial island has been built in shallow water that can accommodate drilling rigs and extended-reach wells. This paper presents a case study of the longest onshore well drilled in Abu Dhabi. Planning to drill such a deep well starts long before execution, using offset well data and extended-reach drilling (ERD) engineering. There were formation and reservoir challenges due to the uncertainty in the earth model in the horizontal section of the well. Hence, it was very challenging to maintain contact with the thin reservoir intervals, without approaching the boundaries. In addition, the limited power available to drive the drillstring and maintain circulation drove the ERD engineering team to find optimum solutions, including drillstring and bottomhole assembly (BHA) design. Furthermore, there was a known risk of differential sticking, which meant that the use of radioactive sources in the BHA was undesirable. The well was planned to be drilled in two runs, using nuclear measurements in the first run and non-nuclear measurements in the second. A well-placement methodology and workflow was developed and integrated with the geological understanding of the target layer. Analysis of offset horizontal wells resulted in the delivery of an optimized BHA design, including careful selection of logging-while-drilling (LWD) technologies, to mitigate the geological challenges. The BHA also included a new generation of intelligent, fully rotating, high-dogleg, push-the-bit rotary-steerable system, to geosteer the well in the thin target layer while maintaining the planned target trajectory with minimum borehole tortuosity by means of real-time drilling optimization. The extended-reach horizontal section was drilled successfully, and the geosteering objectives were achieved with 100% reservoir contact over a 20,000-ft interval, targeting a thin carbonate layer and overcoming the complex geological environment. The well was drilled to a record depth of 32,300 ft. The new intelligent rotary steerable system with automatic cruise control helped to eliminate any well-profile issues, minimize wellbore tortuosity, and maintain aggressive drilling parameters. The nuclear and non-nuclear LWD measurements, including NMR, helped to reinforce understanding of the reservoir properties along the entire section. This success has opened the door for drilling more challenging wells. In addition, it has proved that proper planning and execution can shift the boundaries further and gave confidence to drill even deeper.
- North America > United States > Montana > Target Field (0.99)
- Asia > Middle East > UAE > Abu Dhabi > Arabian Gulf > Rub' al Khali Basin > Abu Dhabi Field (0.97)
Abstract Carbonate matrix acidizing creates wormholes in the damaged formation around the wellbore and is used extensively to enhance well productivity. There are many factors discussed in literature that can positively or negatively affect the efficiency of carbonate matrix acidizing, such as mineralogy, permeability, porosity, and factors associated with the rock matrix and the acidizing fluids. However, the influence of reservoir crude oil on the acidizing operation has not been addressed and is the subject of this study. Several limestone outcrop samples were selected and used in this study after evaluation of their petrophysical properties. The samples were fully saturated with deionized water; some samples were centrifuged and aged at high-pressure/high-temperature (HP/HT) conditions with different grades of crude oils. Linear acidizing experiments were executed; the preliminary acidizing tests showed optimal flow rate of 2 cm/min. A baseline test was then conducted, using preflush fluid injection prior to acidizing to represent the real scenario of a stimulation job in the reservoir. The preflush helped to clean out the rock matrix, preparing the sample for acid injection. Lower pore volume before breakthrough (PVBT) was observed compared to the preliminary tests without the preflush. Then, linear acidizing tests were run on oil-saturated core samples. The results showed that the lower crude oil API is, the less acid volume needed to achieve acid breakthrough. This is mainly due to the viscous fingering that occurs because of the high viscosity contrast between the low-API crude oil and the 15% HCl acid used. These results show the impact of crude oils with different API on the acidizing efficiency, which is very important information for reservoir engineers and should help proper planning the potential volume of acid needed and in making the right operational decisions for better financial impact.
- Asia > Middle East (0.68)
- North America > United States > Texas (0.47)
Case Study Artificial Intelligence (AI) Assisted Numerical Reservoir Simulations in a Mature Reservoir Under Waterflood Development in the Sultanate of Oman
Shuaibi, Fakhriya Abdullah (Petroleum Development Oman) | Hadhrami, Munira Mohamed (Petroleum Development Oman) | Sheheimi, Awadh Harbouq (Petroleum Development Oman) | Agarwal, Binayak (Petroleum Development Oman) | Riyami, Qassim Mohamed (Petroleum Development Oman) | Ruqaishi, Mohammed (Petroleum Development Oman) | Habsi, Naima (Petroleum Development Oman) | Mortezazadeh, Emad (Target Oilfield Services LLC) | Mohajeri, Sina (Target Oilfield Services LLC)
Abstract PDO is transforming its field development planning by adopting digital technologies and Artificial Intelligence (AI) to improve organizational efficiency and maximize business value through swift quality decisions and an evergreen forecast. In this context, the company has approached a number of third parties to bring in solutions in this domain. In 2021 one such collaboration with 3rd party contractor to test a novel solution involving data driven AI based dynamic simulator in a mature brown fiend setting. The objective was to test the tool, the efficacy and efficiency of the process, robustness and ease of use and its utility in current setting [1]. Existing dynamic modelling workflows with conventional simulators are extremely time consuming to update and upgrade in a mature brownfield setting. These conventional and lengthy iterative process of working might leave value on the table. It is time consuming to update history match with all the extra inputs and forecast; and optimizing the development with all the input parameters within a short timeframe is always a challenge. The process employed in this approach was based on deep learning artificial neural networks (ANN) coupled with numerical simulators and along other static model inputs. The reservoir static and the flow dynamics were used as feature parameters to train the ANN, while the historical field production was used as the target parameters. The ANN training exercise identified the most contributed static and dynamic parameters to the historical production; therefore, these main parameters were given a higher weight in production forecasting and reservoir management. This AI-simulation method was expected to be faster, data driven and allow a faster testing of multiple development strategies in short time. This paper outlines the experience of an AI-assisted numerical simulation approach to unlock the potential of brown oil fields in south Oman by reducing the time spent on modelling and base case anchoring. It also enables evergreen forecasting by integrating AI techniques with numerical simulation. The AI-simulation was tried in a brown field with an existing FDP generated using conventional simulation tool where >50% of the FDP propose wells have been drilled. The outcomes from the AI-simulation result were compared with conventional simulation and with Actual field performance. Optimization was also conducted to locate the sweet spots for future drilling and WRFM opportunities. This optimized workflow has the potential to enable step change improvements in time and value for brownfield development and optimization for future developments.
- Asia > Middle East > Oman (0.61)
- North America > United States > Texas > Terry County (0.54)
- North America > United States > Texas > Gaines County (0.54)
- Europe > United Kingdom > North Sea > Southern North Sea (0.54)
Takamul: A Digital Solution to Manage New Oil Performance from End-to-End
Al Shabibi, Hilal (Petroleum Development Oman) | Ghulam, Junaid (Petroleum Development Oman) | Al Azri, Nasser (Petroleum Development Oman) | Mohammed, Mushtaq (Petroleum Development Oman) | Sheheimi, Awadh (Petroleum Development Oman) | Al Khabouri, Khalid (Target) | Al Raisi, Amina (Target)
Abstract In any E&P organization, drilling new wells is part of field development activity. This allows company to bring into production additional oil from different fields. Number of new wells drilled varies from company to company from a few to hundreds as in case of Petroleum Development Oman (PDO). Drilling new wells is a capital-intensive activity. Contribution to the overall production from new wells makes for higher returns on investment. New oil production, is an integrated activity involving a number of departments and different stakeholders. Information and data come from different sources and has to be validated by different stakeholders. Over the years, this has been done in a traditional manner with smart use of spreadsheets. However, with increase in activity, this way of working became cumbersum and time consuming. In business planning, it is important to select an optimum set of activities for drilling which will generate most new oil from allocated resources and budget. It should also be able to quantify opportunity oil in changing requirements. This means generating alternative sequences and comparing them against a set of KPIs and constraints. This exercise is required to be carried out within a cluster and across different clusters in a business unit. With the use of smart spreadsheets, this was getting difficult and time consuming. Resulting in suboptimal drilling sequence and missed opportunity to increase New Oil production.
Application of a Rigorous Scale Prediction Workflow to the Analysis of CaCO3 Scaling in an Extreme Acid Gas, High Temperature, Low Watercut Onshore Field in Southeast Asia
Ness, Giulia (Flow Confidimus) | Sorbie, Kenneth S (Heriot-Watt University) | Gough, Mark (Clariant Oil Services Indonesia) | Akbar, Rifky (Clariant Oil Services Indonesia) | Wylde, Jonathan J (Clariant OMS Houston) | Thornton, Alex (Clariant OMS Houston)
Abstract Calcium carbonate is a pH dependent inorganic mineral scale that is influenced by CO2 and H2S partitioning. CaCO3 prediction must therefore include accurate modelling of the aqueous phase and all hydrocarbon phases present. pH dependent scale prediction challenges and the development of a rigorous procedure for generation of more accurate results were previously published. This procedure has now been applied to an onshore oilfield in Southeast Asia for assessment and management of CaCO3 scaling. A rigorous scale prediction workflow was applied to ‘at-risk’ field producers that showed CaCO3 scaling at and/or downstream of the wellhead choke valve (WHCV). By inputting relevant field data into an integrated PVT/scale prediction code and using the correct procedure, it was possible to evaluate scaling potentials. A series of sensitivity studies allowed well ranking based on the predicted severity of their scaling potentials. The approach validated mechanistic hypotheses for scale development in prolific low watercut, ultra-high CO2, sour, high temperature producers. Close matching of predictions with actual wellhead scaling events provided the basis for improved full-field scale management, and strategic targeting of onsite scale mitigation resources. Target field producers exhibited 0.2% to 25% watercut and presented different degrees of scale precipitation at and/or downstream of the WHCVs. Following well scaling potential assessment, each producer was subject to a series of sensitivity studies to identify (i) how scaling changed with time and (ii) provide focus on the key inputs that most impacted predictions. The initial findings, considering measurement errors (normal field variability), were surprising as key input parameters such as gas phase CO2 and produced water calcium ion concentration appeared to show minimal influence on the final scale prediction results for these wells; even more remarkable considering typical production featured very low salinity produced brine and ultra-high CO2 sour field gas. Focus was therefore shifted to field temperatures, pressure profiles and volumetric flow rates. Of importance is that the selection of ‘critical parameters’ is field specific and that the example presented here shows the variability in scale precipitation at different stages of well production, and how the scaling potential (SR and mg/L) must be evaluated together with the predicted daily theoretical mass of scale (kg/d). This is important in the study of wells with such variable water cut. The following paper demonstrates the value of a rigorous and systematic approach to the prediction of CaCO3 scale, which is often investigated using inappropriate or incomplete methodologies. In this work the authors demonstrate how the technique can address and explain important operational issues and provide solid foundations for implementing and indeed improving the field scale management program.
- Asia (1.00)
- North America > United States > Texas (0.68)
- North America > United States > Montana > Roosevelt County (0.24)
Abstract The purpose of this study is to develop and verify an alternative spread mooring system to be applied to FLNG operated in West Africa. Time domain analysis for ULS (ultimate limit state) and ALS (accidental limit state) design and frequency domain analysis for FLS (fatigue limit state) design were carried out to evaluate the feasibility of the developed mooring system. Side-by-side offloading analysis was also performed to ensure that FLNG equipped with the proposed mooring system can meet the operability requirement of the offloading operation.