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Petroleum Engineering, University of Houston, 2. Metarock Laboratories, 3. Department of Earth and Atmospheric Sciences, University of Houston) 16:00-16:30 Break and Walk to Bizzell Museum 16:30-17:30 Tour: History of Science Collections, Bizzell Memorial Library, The University of Oklahoma 17:30-19:00 Networking Reception: Thurman J. White Forum Building
- Research Report > New Finding (0.93)
- Overview (0.68)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Mineral (0.72)
- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (0.68)
- (2 more...)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (0.93)
- North America > United States > Texas (1.00)
- Europe (0.93)
- Research Report > New Finding (0.93)
- Overview (0.88)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (0.68)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.47)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (0.93)
Abstract The importance of interpretation through DFITs in characterizing reservoirs is widely recognized, leading to their incorporation into major commercial PTA software packages. However, certain limitations inherent in classical methodologies, especially for low-permeability reservoirs, have been overcome through the adoption of type-curve interpretation methodologies (Craig, 2014), and whose advantages have been exposed by Gonzalez and Arhancet (2022). Given the complexity and lack of available tools for employing this methodology, a hybrid team with technical and programming expertise developed a Python application that facilitates the integration of this new methodology and makes it accessible to all technical staff within the company, increasing efficiency and saving costs. The use of type-curve methodology offers a significant advantage in the interpretation of initial pressures, transmissibility, and permeability in low-permeability reservoirs, which could not be obtained using classical techniques. Until now, this new workflow has been carried out using spreadsheets in a handmade and rudimentary manner, requiring considerable time from the user. Although the data is often available, spreadsheets methodology makes interpretation difficult for end users, and it is very time compsuming. To address this issue, an ad hoc Python application was developed, using popular libraries such as pandas and matplotlib. This application allows users to interact with multiple screens to load and preprocess data in an agile, intuitive, and standardized manner. The development of an application with a standardized and well-organized workflow significantly improves the quality and efficiency of interpretation, especially for users with less experience. Having such a tool reduces the need to understand the functioning of spreadsheets and decreases the possibility of errors. The use of this application allows for maintaining an updated database with more than 200 records in a consistent manner. In addition to the benefit related to data interpretation, in-house hybrid team development allowed for faster time to value and enabled the tool to be developed in an agile manner, adapting to business needs. This means lower costs compared to other development methods, such as hiring a programming company or adopting commercial software. Having a tool that is currently not available in commercial software allowed for the consolidation of this methodology, which was already being used in a more handmade way and enabled the valuation of a large number of DFITs that could not be interpreted with the classical methodology. Having updated databases improves the quality of subsequent analyses (correlations, mappings, etc.). The tool has both the classical and type curve methodologies in a single environment, allowing the user to perform a complete analysis without the need for other software. In future steps, an upgrade will be made to include interpretation of post-frac fall offs. And although the application was born for a specific need for unconventional formations, its use can be extrapolated to any formation type.
- North America > United States > Texas (0.47)
- South America > Argentina > Patagonia Region (0.41)
- South America > Argentina > Neuquén Province > Neuquén (0.41)
- North America > Canada > Alberta (0.28)
- South America > Argentina > Patagonia > Neuquén > Neuquen Basin > Vaca Muerta Shale Formation (0.99)
- South America > Argentina > Patagonia > Neuquén > Neuquen Basin > Vaca Muerta Field > Vaca Muerta Shale Formation (0.98)
Increasing the Oil Production Coefficient of Oil and Gas Reservoirs Operating in The Dissolved Gas Mode
Mammadova, G. G. (Azerbaijan State Oil and Industry University, Baku, Azerbaijan) | Abbasova, S. V. (Azerbaijan State Oil and Industry University, Baku, Azerbaijan) | Abbaszade, E. E. (Azerbaijan State Oil and Industry University, Baku, Azerbaijan)
Abstract Depending on the daily gas production, the character of the pressure dynamics in the field and the movement of the gas-water contact should be determined in order to provide a project for the development of gas fields. The change of those factors mainly depends on the regime of the bed. In the dissolved gas regime, the only driving force is the elastic energy of gas dissolved in oil. When gas-cut liquid (oil) moves in the formation, the relative permeability of the formation for gas and oil depends on its oil saturation factor. The saturation coefficient depends on the amount of oil and gas extracted from the reservoir and reservoir pressure. Therefore, since the movement under the dissolved gas drive mode is complex and undetermined, approximate methods to solve hydrodynamic problemsare used.
- Reservoir Description and Dynamics > Reservoir Characterization (1.00)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Drillstem/well testing (0.91)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (0.70)
First Unconventional Najmah Horizontal Well in Green Jurassic Gas Field Unlocked the Reservoir Potential and Setup Development Strategy Roadmap
Abdel-Basset, M. (SLB, Kuwait) | Al-Otaibi, Y. (Kuwait Oil Company, Kuwait) | Al-Ajmi, S. (Kuwait Oil Company, Kuwait) | Al-Mulla, S. (Kuwait Oil Company, Kuwait) | Bloushi, T. (Kuwait Oil Company, Kuwait) | Al-Mutawa, M. (Kuwait Oil Company, Kuwait) | Al-Ajmi, M. (Kuwait Oil Company, Kuwait) | Hadi, A. (Packers Plus Energy Services, Kuwait)
Abstract The journey of appraising unconventional reservoirs of North Kuwait Jurassic Gas (NKJG) fields achieved a significant milestone through the successful test in the first horizontal well completed in Najma Limestone (NJ-LS) reservoir in Bahra field. This accomplishment becomes even more remarkable given that none of the previous vertical wells’ tests were successful. This paper will demonstrate the challenges faced in the well placement, completion and stimulation, as well as the implementation of new technologies to achieve Kuwait’s highest ever initial gas production rate. This outstanding success in appraisal well has unlocked the potential of the NJ-LS reservoir and prompted a step-change in its development strategy. NJ-LS is a tight gas-condensate reservoir with typical porosity ranging from 2 to 9% and very low matrix permeability (~0.01mD) with primary production through natural fractures. To increase the chances of success in encountering fracture corridors, long drain-hole horizontal wells were deemed necessary. To overcome well planning and placement challenges, detailed seismic attribute mapping and integration of available core and log data were undertaken to place the well in the best sweet spot. Extensive screening of seismic data helped avoid possible seismically mappable hazards and optimize the trajectory to encounter areas with high fracture corridor. The well was drilled as 6in lateral length of approximately 2900ft and successfully landed as planned. State-of-the-art drilling and real-time geosteering technologies aided in precisely placing the wellbore in the target zone of NJ-LS. The integrated completion design included eight stages of Multi-Stage Completion, as first-time achievement in NKJG fields. The targeting of shorter stages aimed to accommodate better the reservoir heterogeneity (matrix, fractures, losses, etc) to improve acid stimulation efficiency. Many operational challenges were faced and overcame by multidisciplinary team during the multi-stage stimulation and flow back (e.g high surface pressure ~12,000 psia and presence of H2S). All eight stages were individually stimulated with high-rate matrix acidizing. Commingle activation, flow back and testing activities were executed in continuous back-to-back operations to fast track well delivery to production. Double degradable balls were used for the first time to open the corresponding FracPORT seat and isolate lower open stages. Two green burners used for the first time in Kuwait, accommodated the high returns during flow back and initial testing. Continued advancements throughout the full well cycle, from well placement to stimulation, culminated in achieving Kuwait’s highest ever gas production rate on the initial test, with low Water-cut at different choke sizes and high Wellhead pressure (+/- 6500 psia) Such outstanding results have encouraged the NKJG asset to fast track the extension of this success to other sweet spots as step-change in unconventional reservoirs, supporting the roadmap towards achieving and sustaining the asset’s production target.
- Asia > Middle East > Kuwait > Jahra Governorate > Arabian Basin > Widyan Basin > North Kuwait Jurassic (NKJ) Fields > Marrat Formation > Upper Marrat Formation (0.99)
- Asia > Middle East > Kuwait > Jahra Governorate > Arabian Basin > Widyan Basin > North Kuwait Jurassic (NKJ) Fields > Marrat Formation > Sargelu Formation (0.99)
- Asia > Middle East > Kuwait > Jahra Governorate > Arabian Basin > Widyan Basin > Bahrah Field > Marrat Formation (0.99)
Modelling Transient Production Forecasting of Horizontal Wells in Abnormal High-Pressure Tight Gas Reservoirs
Cao, Lina (Research Institute of Exploration and Development, China ZhenHua Oil Co., Ltd., Chengdu, China) | Wang, Hehua (Research Institute of Exploration and Development, China ZhenHua Oil Co., Ltd., Chengdu, China) | Jiang, Liping (Research Institute of Exploration and Development, China ZhenHua Oil Co., Ltd., Chengdu, China) | Zhang, Bo (EBS Petroleum Company Limited, Iraq) | Ganzer, Leonhard (Institute of Subsurface Energy Systems, Clausthal University of Technology, Germany) | Li, Ying (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, China) | Wang, Xiaochao (CNOOC EnerTech-Drilling & Production Co., Tianjin, China) | Li, Ke (Institute of Subsurface Energy Systems, Clausthal University of Technology, Germany) | Pang, Siyu (Institute of Subsurface Energy Systems, Clausthal University of Technology, Germany) | Xiao, Heng (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, China)
Abstract Natural gas stands out as a cleaner source of energy due to its relatively lower carbon emissions, making it an appealing choice for numerous countries. Therefore, it is essential to gain a deeper understanding of natural gas reservoirs to ensure sustainable extraction and unlock their full potential. The behavior of fluid flow and production in complex gas reservoirs, especially those characterized by abnormal high-pressure and tight porous media, is not yet fully comprehended, necessitating further investigation. Traditional Darcy's law is no longer applicable in tight porous media with high pressure. To overcome this challenge, a new composite seepage model was developed. The model incorporates stress-sensitive permeability and threshold pressure gradient. We employed perturbation theory for permeability modulus and the Green function method for the inhomogeneous special solution, effectively addressing its nonlinearity. Through integration transformation methods, a dimensionless rate solution under constant bottom-hole pressure was derived in the Laplace domain. Eventually, a new model involving multiple factors has been proposed for production prediction in such gas reservoirs. Studying unsteady gas flow dynamics in tight formations provides valuable insights into flow patterns. To investigate transient flow characteristics in tight gas reservoirs, log-log figures were generated through Stehfest numerical inversion. Flow periods were classified based on standardized time stages for rate curves. A parametric study revealed that stress sensitivity damages permeability, causing a larger pressure drop in intermediate and late flow regimes. This effect is reflected in upward tendencies in rate derivative curves. A higher threshold pressure gradient indicates poorer reservoir properties, making fluid flow more difficult, as evidenced by steeper downwarping in production rate curves. The combined impact of stress-sensitivity and threshold pressure gradient accentuates the variation trend in these curves. Multi-stage hydraulic fracturing can effectively address the negative impacts of these two factors, which impede seepage. Enhancing fracture conductivity can decrease even eliminate the threshold pressure gradient, while increasing proppant strength can slow down elastic and plastic deformation of reservoir rock, thereby reducing the loss of permeability. The transient seepage model developed in this paper serves not only for production prediction but also to explain the related formation and well parameters. It functions as a traditional well test interpretation tool, particularly remarkable as it relies solely on daily production data, enhancing workflow efficiency and reducing testing time. The interpreted parameters are valuable for designing hydraulic fracturing operations, evaluating the potential of tight gas reservoirs, and ultimately increasing gas production rates.
Abstract In the context of climate change, one way to reduce atmospheric emissions of carbon dioxide is Carbon Capture and Storage (CCS) in both depleted hydrocarbon reservoirs and saline aquifers. The injectivity index is one of the most important parameters to monitor and forecast carbon storage; it determines how rapidly CO2 can be injected, which then determines the rate of storage. This paper verifies the feasibility of a methodology to monitor the well injectivity of a CO2 injector well during its lifetime. In the oil industry, this is based on the acquisition of downhole pressure and temperature during a well test that is interpreted using Pressure Transient Analysis (PTA). Here we investigate if the same techniques could be applied to CO2 injection, considering the complex interaction between CO2, rock, and reservoir fluids. The study was performed running a simplified full-scale reservoir compositional model, representative of a depleted gas reservoir of an Eni CCS project. The so generated bottomhole flowing pressures, were analyzed using PTA to estimate the mechanical skin factor, accounting for the reduction in permeability near the wellbore, which potentially limits the amount of CO2 that can be injected. The work confirmed that the monitoring of the bottom-hole pressure through permanent downhole gauges or even with temporary acquisition memory gauges run-in-hole with a slick-line is crucial for the monitoring in real-time of the well injectivity. Analytical PTA tools provide a sound characterization of the well status: static pressure, permeability-thickness product, permeability, and mechanical skin. Under the assumptions of this study, no significant skin component due to the interaction of the CO2-rock-reservoir fluids was detected; its presence may be apparent in more complex scenarios (i.e., considering induced salt precipitation).
Interpretation of Rayleigh Frequency Shift Based Distributed Strain Sensing Data During Production and Shut-In of Unconventional Reservoirs
Ou, Yuhao (The University of Texas at Austin, Austin, TX, USA) | Hu, Jinchuan (The University of Texas at Austin, Austin, TX, USA) | Zheng, Shuang (Aramco, Houston, TX, USA) | Sharma, Mukul (The University of Texas at Austin, Austin, TX, USA)
Abstract A new fiber optic measurement, Distributed Strain Sensing based on Rayleigh Frequency Shift, (DSS-RFS) was recently applied to wells in unconventional reservoirs. During production operations, strain changes are measured with high spatial resolution and sensitivity. The objective of this paper is to show that it is possible and very useful to simulate and interpret these strain change plots to identify locations of producing perforation clusters and gain new insights into near wellbore fracture geometry. DSS-RFS fiber optic data is modeled during production from an unconventional reservoir. A fully coupled geomechanical fracture-reservoir simulator is used to simulate full lifecycle of hydraulic fractured horizontal wells, which incorporates the creation of hydraulic fractures with proppant injection, post-frac closure, primary production, cycles of production, shut-in and reopening. An implicit contact force model is implemented for modeling proppant embedment regarding fracture width change during fracture closure and pressure depletion. DSS-RFS plots are generated by obtaining the strain change along the wellbore during production. The simulations are then used to interpret the measurements in terms of pore pressure depletion and near wellbore fracture geometry. The simulated results match well with DSS-RFS data measured in the field. The tensional strain change signals correspond to the locations of active clusters, and the effect of pressure depletion is consistently seen in the simulations. This allows us to quantitatively interpret the measured DSS strain change in terms of the extent of pore pressure depletion during production. The strain change is also found to be related to near wellbore fracture geometry: (1) peak values of the tensional signals are positively correlated with near wellbore fracture width; (2) a larger simulated reservoir volume around a fracture leads to a wider positive strain change signal; (3) the height of the transition zone between active clusters is strongly related to reservoir depletion with respect to both space and time; (4) the height of the extensional signals can be used to assess production allocation among clusters when proppant injection distribution is relatively uniform during fracturing; (5) the shape the extensional signal becomes non-symmetric when there is a large depletion contrast on two sides of a fracture. A series of parameter sensitivity simulation results are analyzed to provide a systematic algorithm for accessing cluster efficiency and production allocation based on DSS-RFS data. The paper presents, a quantitative analysis for assessing cluster efficiency, location of active and inactive clusters and the extent of pore pressure depletion in a horizontal well using DSS-RFS strain change data. In addition, information about near wellbore fracture geometry can be inferred. This is made possible by a new and unique modeling capability that models the entire lifecycle of crack propagation with realistic fracture width and proppant volume distribution (considering stress shadow effects) as well as fluid production and well shut-in.
- Geophysics > Seismic Surveying (0.46)
- Geophysics > Borehole Geophysics (0.46)
- North America > United States > Texas > Permian Basin > Delaware Basin (0.99)
- North America > United States > New Mexico > Permian Basin > Delaware Basin (0.99)
- Well Completion > Hydraulic Fracturing > Fracturing materials (fluids, proppant) (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Reservoir geomechanics (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Drillstem/well testing (1.00)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring > Production logging (1.00)
Abstract An analytical solution is presented for pressure- and rate-transient behavior of an array of, parallel, fractured horizontal wells in an unconventional reservoir. Wells are of equal length but otherwise of unidentical properties. Each well has an arbitrary number of uniformly spaced identical, finite-conductivity fractures and is surrounded by a stimulated reservoir volume. Properties of hydraulic fractures and stimulated reservoir volumes may vary from well to well. Different properties may also be assigned to unstimulated reservoir section between wells. Natural fractures in the stimulated and unstimulated reservoir volumes are accounted for by the transient dual-porosity idealization. Flow domain is divided into blocks of one-dimensional flow under the trilinear flow assumption. Analytical solution for each block is obtained by the appropriate Green's function and coupled with the neighboring blocks by the continuity of pressure and flux at the block interfaces. Superposition principle is applied to consider variable production conditions as well as nonsynchronous production and shut-in schedules of wells. The final solution is in the form of a matrix-vector equation in the Laplace transform domain and inverted into time-domain numerically. Results are robust and reasonably accurate for most practical applications of single-phase oil and gas production from multiple wells in an unconventional reservoir. The solution provides an efficient tool to assess well interference effects for different well completion designs and varying reservoir characteristics. The speed of calculations is convenient for pressure-transient and production-data analysis, as well as for the initial calibration and verification of more complex numerical models. The closed analytical form of the solution enables assessment of flow regime diagnostics under well-interference.
A Novel Hierarchical Global-Local Model Calibration Method for Deep Water Reservoirs Under Depletion and Aquifer Influence
Li, Ao (Texas A&M University, College Station, Texas, USA) | Alpak, Faruk Omer (Shell International Exploration and Production Inc., Houston, Texas, USA) | Jimenez, Eduardo (Shell International Exploration and Production Inc., Houston, Texas, USA) | Yeh, Tzu-Hao (Shell International Exploration and Production Inc., Houston, Texas, USA) | Ritts, Andrew (Shell International Exploration and Production Inc., Houston, Texas, USA) | Jain, Vivek (Shell International Exploration and Production Inc., Houston, Texas, USA) | Chen, Hongquan (Texas A&M University, College Station, Texas, USA) | Datta-Gupta, Akhil (Texas A&M University, College Station, Texas, USA)
Abstract An ensemble of rigorously history matched reservoir models can help better understand the interactions between heterogeneity and fluid flows, improve forecasting reliability, and locate infill-drilling opportunities to support field development plans. However, developing efficient calibration methods for complex, multi-million cell deep-water models remains a challenge. This paper presents a hierarchical global-local assisted-history matching (AHM) approach with new elements, applied to a complex deep-water reservoir. The new AHM method consists of two stages: global and local. In the global stage, the reservoir energy is matched using an evolutionary approach to calibrate the model parameters with build-up and average reservoir pressures. Instead of using regional/box multipliers, we use parameters that are in line with geologic and engineering data across the reservoir. In the local stage, local updates are made to reservoir heterogeneity to match water cut in a geologically continuous manner. The permeability field is calibrated to production data using a novel streamline-based sensitivity-driven AHM method to ascertain the spatial variability and geologic continuity of local updates. The sensitivity for each streamline is weighted by the water fraction and constrained by a time-of-flight cutoff to focus on water intrusion regions within the near wellbore region. The resulting method is physically intuitive and easy to implement in practice. The hierarchical AHM method is field-tested in a complex deep-water reservoir. Associated challenges from model-calibration perspective are multiple saturation-function/PVT regions, uncertain sand connectivity, multi-sand well penetrations, a long reservoir history, and depletion-driven recovery under the influence of an aquifer. The method is applied to match data including build-up/reservoir pressures, oil production rates, and water cut. The evolutionary approach generates an ensemble of models with well-matched oil production rates and build-up/reservoir pressure using global model parameters. Local updates using streamline-based gradients are then conducted to match the water cut for each ensemble member while maintaining overall pressure match quality. Results show that the hierarchical AHM method significantly reduces the data misfit and is well-suited to primary recovery in a deep-water setting with few producers and under the influence of mild/weak aquifers. The new developments in the local stage make the entire workflow more robust because ensuing variations do not disrupt the global match quality for problems without a strong coupling between pressure and saturation physics. The novelty of the proposed method lies in the streamline-based sensitivity computation method modified for use in history matching deep-water reservoirs undergoing depletion under mild/weak aquifer influence. Using a two-stage global-local AHM workflow, the proposed method is robust, efficient, and straightforward to implement and deploy.
- Asia (0.93)
- North America > United States > Texas (0.47)
- Europe > United Kingdom > North Sea > Northern North Sea > East Shetland Basin > License P2501 > Block 3/29a > Rhum Field > R2 Well (0.99)
- Europe > United Kingdom > North Sea > Northern North Sea > East Shetland Basin > License P2501 > Block 3/29a > Rhum Field > R1 Well (0.99)
- Asia > India > Rajasthan > Rajasthan Basin > Barmer Basin > Rajasthan Block > Mangala Field > Fatehgarh Formation (0.99)
- (4 more...)
- Reservoir Description and Dynamics > Reservoir Simulation > History matching (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery (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)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Search (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Evolutionary Systems (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Optimization (0.93)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.93)