Finding the Best of the Best: Hydraulic Fracturing Design Optimization Study in Oman

2022 ◽  
Author(s):  
Rifat Kayumov ◽  
Ahmed Al Shueili ◽  
Musallam Jaboob ◽  
Hussain Al Salmi ◽  
Ricardo Sebastian Trejo ◽  
...  
Keyword(s):  
Hydraulic Fracturing ◽  
Pressure Gauge ◽  
Design Sensitivity ◽  
Actual Data ◽  
Earth Model ◽  
Reservoir Properties ◽  
Sector Model ◽  
Optimization Study ◽  
Exploration And Production ◽  
Reservoir Simulator

Abstract Development of the tight gas Khazzan Field in Sultanate of Oman has progressed through an extensive learning curve over many years. Thereby, the hydraulic fracturing design was fine-tuned and optimized to properly fit the requirements of the challenging Barik reservoir in this area. In 2018, BP Oman started developing the Barik reservoir in the Ghazeer Field, which naturally extends the reservoir boundary south of Khazzan Field. However, the Barik reservoir in the Ghazeer area is thicker and more permeable than in the Khazzan Field; therefore, the hydraulic fracturing design required adjustment to be optimized to directly reflect the reservoir needs of the Ghazeer Field. A comprehensive hydraulic fracturing design software was used for this optimization study and sensitivity analysis. This software is a plug-in to a benchmark exploration and production software platform and provides a complete fracturing optimization loop from hydraulic fracturing design sensitivity modelled with a calibrated mechanical earth model to detailed production prediction using the incorporated reservoir simulator. One of the stimulated wells from Ghazeer Field was used as the reference for this study. The reservoir sector model was created and adjusted to match actual data from this well. The data include fracturing treatment execution response, surveillance data such as radioactive tracers, bottomhole pressure gauge, and pressure transient analysis. Reservoir properties were also adjusted to match long-term production data obtained for this reference well. After the reservoir model was fully validated against actual data, multiple completion and fracturing scenarios were simulated to estimate potential production gain and thus find an optimal hydraulic fracturing design for Ghazeer Field. Many valuable outcomes can be concluded from this study. The optimal treatment design was identified. The value of fracture half-length versus conductivity was clarified for this area. The comparison between single-stage fracturing versus multistage treatment across the thick laminated Barik reservoir in a conventional vertical well was derived. The drainage of different layers with variable reservoir properties was compared for a range of different scenarios.

Joint Application of Diagenetic, Petrophysical and Geomechanical Data for Selecting Hydraulic Fracturing Candidate Zone

2021 ◽  
Vol 8 ◽  
pp. 55-79
Author(s):  
E. Bakhshi ◽  
A. Shahrabadi ◽  
N. Golsanami ◽  
Sh. Seyedsajadi ◽  
X. Liu ◽  
...  
Keyword(s):  
Hydraulic Fracturing ◽  
Pore Pressure ◽  
Earth Model ◽  
Reservoir Properties ◽  
Stress Regime ◽  
Geomechanical Properties ◽  
Hydrocarbon Reservoir ◽  
Diagenetic Processes ◽  
Mechanical Earth Model ◽  
New Equation

The more comprehensive information on the reservoir properties will help to better plan drilling and design production. Herein, diagenetic processes and geomechanical properties are notable parameters that determine reservoir quality. Recognizing the geomechanical properties of the reservoir as well as building a mechanical earth model play a strong role in the hydrocarbon reservoir life cycle and are key factors in analyzing wellbore instability, drilling operation optimization, and hydraulic fracturing designing operation. Therefore, the present study focuses on selecting the candidate zone for hydraulic fracturing through a novel approach that simultaneously considers the diagenetic, petrophysical, and geomechanical properties. The diagenetic processes were analyzed to determine the porosity types in the reservoir. After that, based on the laboratory test results for estimating reservoir petrophysical parameters, the zones with suitable reservoir properties were selected. Moreover, based on the reservoir geomechanical parameters and the constructed mechanical earth model, the best zones were selected for hydraulic fracturing operation in one of the Iranian fractured carbonate reservoirs. Finally, a new empirical equation for estimating pore pressure in nine zones of the studied well was developed. This equation provides a more precise estimation of stress profiles and thus leads to more accurate decision-making for candidate zone selection. Based on the results, vuggy porosity was the best porosity type, and zones C2, E2 and G2, having suitable values of porosity, permeability, and water saturation, showed good reservoir properties. Therefore, zone E2 and G2 were chosen as the candidate for hydraulic fracturing simulation based on their E (Young’s modulus) and ν (Poisson’s ratio) values. Based on the mechanical earth model and changes in the acoustic data versus depth, a new equation is introduced for calculating the pore pressure in the studied reservoir. According to the new equation, the dominant stress regime in the whole well, especially in the candidate zones, is SigHmax>SigV>Sighmin, while according to the pore pressure equation presented in the literature, the dominant stress regime in the studied well turns out to be SigHmax>Sighmin>SigV.  

Optimization of Smart Wells in the St. Joseph Field

2010 ◽  
Vol 13 (04) ◽  
pp. 588-595 ◽  
Author(s):  
G. M. van Essen ◽  
J. D. Jansen ◽  
D. R. Brouwer ◽  
S. G. Douma ◽  
M. J. Zandvliet ◽  
...  
Keyword(s):  
Optimization Technique ◽  
Gas Injection ◽  
Optimal Number ◽  
Control Parameters ◽  
Operational Strategies ◽  
Sector Model ◽  
Optimization Study ◽  
Smart Wells ◽  
Gradient Based ◽  
Reservoir Simulator

Summary The St. Joseph field has been on production since September 1981 under natural depletion supported by crestal gas injection. As part of a major redevelopment study, the scope for waterflooding was addressed using "smart" completions with multiple inflow control valves (ICVs) in the wells to be drilled for the redevelopment. Optimal control theory was used to optimize monetary value over the remaining producing life of the field, and in particular to select the optimal number of ICVs, the optimal configuration of the perforation zones, and the optimal operational strategies for the ICVs. A gradient-based optimization technique was implemented in a reservoir simulator equipped with the adjoint functionality to compute gradients of an objective function with respect to control parameters. For computational reasons, an initial optimization study was performed on a sector model, which showed promising results.

Machine learning for geophysical characterization of brittleness: Tuscaloosa Marine Shale case study

2020 ◽  
Vol 8 (3) ◽  
pp. T589-T597 ◽  
Author(s):  
Mark Mlella ◽  
Ming Ma ◽  
Rui Zhang ◽  
Mehdi Mokhtari
Keyword(s):  
Machine Learning ◽  
Hydraulic Fracturing ◽  
Rock Physics ◽  
Physical Models ◽  
Data Sets ◽  
Reservoir Properties ◽  
Data Set ◽  
Geomechanical Properties ◽  
Marine Shale ◽  
Exploration And Production

Brittleness is one of the most important reservoir properties for unconventional reservoir exploration and production. Better knowledge about the brittleness distribution can help to optimize the hydraulic fracturing operation and lower costs. However, there are very few reliable and effective physical models to predict the spatial distribution of brittleness. We have developed a machine learning-based method to predict subsurface brittleness by using multidiscipline data sets, such as seismic attributes, rock physics, and petrophysics information, which allows us to implement the prediction without using a physical model. The method is applied on a data set from Tuscaloosa Marine Shale, and the predicted rock physics template is close to the calculated value from conventional inverted elastic parameters. Therefore, the proposed method helps determine areas of the reservoir that have optimal geomechanical properties for successful hydraulic fracturing.

Advanced Multi-Disciplinary Simulation Workflow for Well Placement, Hydraulic Fracturing and Production Optimization Applied to the Diyab Unconventional Play in Onshore UAE

2021 ◽  
Author(s):  
Hamid Pourpak ◽  
Samuel Taubert ◽  
Marios Theodorakopoulos ◽  
Arnaud Lefebvre-Prudencio ◽  
Chay Pointer ◽  
...  
Keyword(s):  
Hydraulic Fracturing ◽  
United Arab Emirates ◽  
Reservoir Characterization ◽  
Horizontal Wells ◽  
Production Optimization ◽  
Production Performance ◽  
Well Placement ◽  
Fully Integrated ◽  
Sector Model ◽  
The Impact

Abstract The Diyab play is an emerging unconventional play in the Middle East. Up to date, reservoir characterization assessments have proved adequate productivity of the play in the United Arab Emirates (UAE). In this paper, an advanced simulation and modeling workflow is presented, which was applied on selected wells located on an appraisal area, by integrating geological, geomechanical, and hydraulic fracturing data. Results will be used to optimize future well landing points, well spacing and completion designs, allowing to enhance the Stimulated Rock Volume (SRV) and its consequent production. A 3D static model was built, by propagating across the appraisal area, all subsurface static properties from core-calibrated petrophysical and geomechanical logs which originate from vertical pilot wells. In addition, a Discrete Fracture Network (DFN) derived from numerous image logs was imported in the model. Afterwards, completion data from one multi-stage hydraulically fracked horizontal well was integrated into the sector model. Simulations of hydraulic fracturing were performed and the sector model was calibrated to the real hydraulic fracturing data. Different scenarios for the fracture height were tested considering uncertainties related to the fracture barriers. This has allowed for a better understanding of the fracture propagation and SRV creation in the reservoir at the main target. In the last step, production resulting from the SRV was simulated and calibrated to the field data. In the end, the calibrated parameters were applied to the newly drilled nearby horizontal wells in the same area, while they were hydraulically fractured with different completion designs and the simulated SRVs of the new wells were then compared with the one calculated on the previous well. Applying a fully-integrated geology, geomechanics, completion and production workflow has helped us to understand the impact of geology, natural fractures, rock mechanical properties and stress regimes in the SRV geometry for the unconventional Diyab play. This work also highlights the importance of data acquisition, reservoir characterization and of SRV simulation calibration processes. This fully integrated workflow will allow for an optimized completion strategy, well landing and spacing for the future horizontal wells. A fully multi-disciplinary simulation workflow was applied to the Diyab unconventional play in onshore UAE. This workflow illustrated the most important parameters impacting the SRV creation and production in the Diyab formation for he studied area. Multiple simulation scenarios and calibration runs showed how sensitive the SRV can be to different parameters and how well placement and fracture jobs can be possibly improved to enhance the SRV creation and ultimately the production performance.

Work Flow History Matches Numerical Simulation Models of Fractured Shale Wells

2021 ◽  
Vol 73 (04) ◽  
pp. 60-61
Author(s):  
Chris Carpenter
Keyword(s):  
Numerical Simulation ◽  
Fracture Toughness ◽  
Hydraulic Fracturing ◽  
History Matching ◽  
Simulation Models ◽  
Work Flow ◽  
Fracture Length ◽  
Matching Process ◽  
Rate Transient Analysis ◽  
Reservoir Simulator

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 199149, “Rate-Transient-Analysis-Assisted History Matching With a Combined Hydraulic Fracturing and Reservoir Simulator,” by Garrett Fowler, SPE, and Mark McClure, SPE, ResFrac, and Jeff Allen, Recoil Resources, prepared for the 2020 SPE Latin American and Caribbean Petroleum Engineering Conference, originally scheduled to be held in Bogota, Colombia, 17–19 March. The paper has not been peer reviewed. This paper presents a step-by-step work flow to facilitate history matching numerical simulation models of hydraulically fractured shale wells. Sensitivity analysis simulations are performed with a coupled hydraulic fracturing, geomechanics, and reservoir simulator. The results are used to develop what the authors term “motifs” that inform the history-matching process. Using intuition from these simulations, history matching can be expedited by changing matrix permeability, fracture conductivity, matrix-pressure-dependent permeability, boundary effects, and relative permeability. Introduction This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 199149, “Rate-Transient-Analysis-Assisted History Matching With a Combined Hydraulic Fracturing and Reservoir Simulator,” by Garrett Fowler, SPE, and Mark McClure, SPE, ResFrac, and Jeff Allen, Recoil Resources, prepared for the 2020 SPE Latin American and Caribbean Petroleum Engineering Conference, originally scheduled to be held in Bogota, Colombia, 17-19 March. The paper has not been peer reviewed. This paper presents a step-by-step work flow to facilitate history matching numerical simulation models of hydraulically fractured shale wells. Sensitivity analysis simulations are performed with a coupled hydraulic fracturing, geomechanics, and reservoir simulator. The results are used to develop what the authors term “motifs” that inform the history-matching process. Using intuition from these simulations, history matching can be expedited by changing matrix permeability, fracture conductivity, matrix-pressure-dependent permeability, boundary effects, and relative permeability. Introduction The concept of rate transient analysis (RTA) involves the use of rate and pressure trends of producing wells to estimate properties such as permeability and fracture surface area. While very useful, RTA is an analytical technique and has commensurate limitations. In the complete paper, different RTA motifs are generated using a simulator. Insights from these motif simulations are used to modify simulation parameters to expediate and inform the history- matching process. The simulation history-matching work flow presented includes the following steps: 1 - Set up a simulation model with geologic properties, wellbore and completion designs, and fracturing and production schedules 2 - Run an initial model 3 - Tune the fracture geometries (height and length) to heuristic data: microseismic, frac-hit data, distributed acoustic sensing, or other diagnostics 4 - Match instantaneous shut-in pressure (ISIP) and wellhead pressure (WHP) during injection 5 - Make RTA plots of the real and simulated production data 6 - Use the motifs presented in the paper to identify possible production mechanisms in the real data 7 - Adjust history-matching parameters in the simulation model based on the intuition gained from RTA of the real data 8 -Iterate Steps 5 through 7 to obtain a match in RTA trends 9 - Modify relative permeabilities as necessary to obtain correct oil, water, and gas proportions In this study, the authors used a commercial simulator that fully integrates hydraulic fracturing, wellbore, and reservoir simulation into a single modeling code. Matching Fracturing Data The complete paper focuses on matching production data, assisted by RTA, not specifically on the matching of fracturing data such as injection pressure and fracture geometry (Steps 3 and 4). Nevertheless, for completeness, these steps are very briefly summarized in this section. Effective fracture toughness is the most-important factor in determining fracture length. Field diagnostics suggest considerable variability in effective fracture toughness and fracture length. Typical half-lengths are between 500 and 2,000 ft. Laboratory-derived values of fracture toughness yield longer fractures (propagation of 2,000 ft or more from the wellbore). Significantly larger values of fracture toughness are needed to explain the shorter fracture length and higher net pressure values that are often observed. The authors use a scale- dependent fracture-toughness parameter to increase toughness as the fracture grows. This allows the simulator to match injection pressure data while simultaneously limiting fracture length. This scale-dependent toughness scaling parameter is the most-important parameter in determining fracture size.

A Proxy Flow Modelling Workflow to Estimate Gridded Dynamic Properties and Well Production Rates by Deep Learning Algorithms

2021 ◽  
Author(s):  
Soumi Chaki ◽  
Yevgeniy Zagayevskiy ◽  
Terry Wong
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Dynamic Properties ◽  
Reservoir Management ◽  
Flow Modeling ◽  
Static Properties ◽  
Production Rates ◽  
Reservoir Properties ◽  
Well Production ◽  
Reservoir Simulator

Abstract This paper proposes a deep learning-based framework for proxy flow modeling to predict gridded dynamic petroleum reservoir properties (like pressure and saturation) and production rates for wells in a single framework. It approximates the solution of a full physics-based numerical reservoir simulator, but runs much more rapidly, allowing users to generate results for a much wider range of scenarios in a given time than could be done with a full physics simulator. The proxy can be used for reservoir management tasks like history matching, uncertainty quantification, and field development optimization. A deep-learning based methodology for accurate proxy-flow modeling is presented which combines U-Net (a variant of convolutional neural network) to predict gridded dynamic properties and deep neural network (DNN) models to forecast well production rates. First, gridded dynamic properties, such as reservoir pressure and phase saturations, are predicted from static properties like reservoir rock porosity and absolute permeability using a U-Net. Then, the static properties and the dynamic properties predicted by the U-Net are input to a DNN to predict production rates at the well perforations. The inclusion of U-net predicted pressure and saturations improves the quality of the well rate predictions. The proposed methodology is presented with the synthetic Brugge reservoir discretized into grid blocks. The U-Net input consists of three properties: dynamic gridded reservoir properties (such as pressure or fluid saturation) at the current state, static gridded porosity, and static gridded permeability. The U-Net has only one output property, the target gridded property (such as pressure or saturation) at the next time step. Training and testing datasets are generated by running 13 full physics flow simulations and dividing them in a 12:1 ratio. Nine U-Net models are calibrated to predict pressures/saturations, one for each of the nine grid layers present in the Brugge model. These outputs are then concatenated to obtain the complete pressure/saturation model for all nine layers. The constructed U-Net models match the distributions of generated pressures/saturations of the numerical reservoir simulator with a correlation coefficient value of approximately 0.99 and above 95% accuracy. The DNN models approximate well production rates accurately from U-Net predicted pressures and saturations along with static properties like transmissibility and horizontal permeability. For each well and each well perforation, the production rate is predicted with the DNN model. The use of the constructed proxy flow model generates reservoir predictions within a few minutes compared to the hours or days typically taken by a full physics flow simulator. The direct connection that is established between the gridded static and dynamic properties of the reservoir and well production rates using U-Net and DNN models has not been presented previously. Using only a small number of runs for its training, the workflow matches the numerical reservoir simulator results with reduced computational effort. This helps reservoir engineers make informed decisions more quickly, resulting in more efficient reservoir management.

scholarly journals Dependences Of Reservoir Oil Properties On Surface Oil

2020 ◽  
Author(s):  
Sudad H Al-Obaidi ◽  
Galkin AP
Keyword(s):  
Hydrodynamic Models ◽  
Reservoir Properties ◽  
High Quality ◽  
Data Dependencies ◽  
Models Of Development ◽  
Production Wells ◽  
Exploration And Production ◽  
High Degree ◽  
Selection Of

Knowledge of the properties of reservoir oil is necessary when calculating reserves, creating projects development, creating hydrodynamic models of development objects. Reservoir oil properties are determined by downhole samples taken, as usual, from exploration and production wells. In some cases, it is impossible to create conditions for the selection of high-quality downhole samples at exploration and production wells. In such cases, we must use samples of surface oil to obtain information about the reservoir properties of this oil. In this work and as a result of the analysis of the accumulated data, dependencies with a high degree of correlation were obtained, which make it possible to quickly assess the expected parameters of reservoir oil, having only the density of surface oil.

Success Story of Optimizing Hydraulic Fracturing Design at Alpha Low-Permeability Reservoir

2021 ◽  
Author(s):  
Mario Hadinata Prasetio ◽  
Hanny Anggraini ◽  
Hendro Tjahjono ◽  
Aditya Bintang Pramadana ◽  
Aulia Akbari ◽  
...  
Keyword(s):  
Hydraulic Fracturing ◽  
Oil Recovery ◽  
History Matching ◽  
Initial Period ◽  
Earth Model ◽  
Low Permeability ◽  
Stress Profile ◽  
Reservoir Pressure ◽  
Fracturing Fluid ◽  
Fracture Closure

Abstract This paper describes the evolution of the hydraulic fracturing approach and design in the Alpha reservoir over the past years. Alpha reservoir in XYZ field is a laminated sandstone reservoir with low permeability in the range of 20 to 140 md at a depth of approximately 4,000 to 4,500 ft true vertical depth (TVD). XYZ field is located in Rokan block, Riau, Central Sumatra region. Due to Alpha reservoir's nature, producing from this reservoir commercially requires stimulation. Hydraulic fracturing has been applied as the selected stimulation method to increase productivity from this reservoir. However, several challenges were recognized during the initial period, such as depleted reservoir pressure, indication of fracture height growth, and low to medium Young's modulus, which leads to few screened-out cases as well as low production gain after the fracturing treatment. The fracturing job in Alpha reservoir has been applied since 2002. However, pressure depletion was observed through this time until waterflood optimization started in May 2018 by converting commingled injection to injection dedicated to the Alpha reservoir. The pressure responded and increased from 350 psi to approximately 800 psi. Hence this reservoir still cannot be produced in single completion without the hydraulic fracturing job due to laminated reservoir and low-permeability character. A detailed look at the mechanical earth model (MEM) was done to revise the elastic properties and stress profile considering reservoir pressure change. The revised model was later used as an input for fracture geometry simulation. Calibration injection tests were performed and analyzed prior to the main fracturing treatments to determine fracture closure pressure and leakoff characteristics, which led to fracturing fluid efficiency. Results of these tests were used in job modifications regarding pad percentage, fracturing fluid rheology, proppant volume, and proppant concentration. Pressure history matching both after fracturing and in real time as well as the temperature log were used to validate the MEM and fracture geometries. Each change, approach, and impact were documented and statistically analyzed to determine a generic trend and design envelope for the Alpha reservoir. Between 2019 and 2020, nine wells were stimulated that specifically targeted the Alpha reservoir, with continuous improvement in fracturing design and geomechanics properties with each well. After fracturing, the 30-day oil recovery was superior, higher than previous fractured wells, reaching more than 255 BFPD on average. The successful development of the Alpha reservoir with hydraulic fracturing led to further milestones to maximize oil recovery in XYZ field.

Applications of quantitative prestack seismic analysis to unconventional resource play characterization in the Permian/Delaware Basin

2019 ◽  
Vol 38 (2) ◽  
pp. 106-115 ◽  
Author(s):  
Phuong Hoang ◽  
Arcangelo Sena ◽  
Benjamin Lascaud
Keyword(s):  
Hydraulic Fracturing ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Seismic Analysis ◽  
Seismic Inversion ◽  
Reservoir Properties ◽  
Yield Attributes ◽  
Horizontal Drilling ◽  
Delaware Basin ◽  
Unconventional Resource

The characterization of shale plays involves an understanding of tectonic history, geologic settings, reservoir properties, and the in-situ stresses of the potential producing zones in the subsurface. The associated hydrocarbons are generally recovered by horizontal drilling and hydraulic fracturing. Historically, seismic data have been used mainly for structural interpretation of the shale reservoirs. A primary benefit of surface seismic has been the ability to locate and avoid drilling into shallow carbonate karsting zones, salt structures, and basement-related major faults which adversely affect the ability to drill and complete the well effectively. More recent advances in prestack seismic data analysis yield attributes that appear to be correlated to formation lithology, rock strength, and stress fields. From these, we may infer preferential drilling locations or sweet spots. Knowledge and proper utilization of these attributes may prove valuable in the optimization of drilling and completion activities. In recent years, geophysical data have played an increasing role in supporting well planning, hydraulic fracturing, well stacking, and spacing. We have implemented an integrated workflow combining prestack seismic inversion and multiattribute analysis, microseismic data, well-log data, and geologic modeling to demonstrate key applications of quantitative seismic analysis utilized in developing ConocoPhillips' acreage in the Delaware Basin located in Texas. These applications range from reservoir characterization to well planning/execution, stacking/spacing optimization, and saltwater disposal. We show that multidisciplinary technology integration is the key for success in unconventional play exploration and development.

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