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.  

Seismic pore pressure prediction with uncertainty using a probabilistic mechanical earth model

2003 ◽  
Author(s):  
P. M. Doyen ◽  
A. Malinverno ◽  
R. Prioul ◽  
P. Hooyman ◽  
S. Noeth ◽  
...  
Keyword(s):  
Pore Pressure ◽  
Earth Model ◽  
Pore Pressure Prediction ◽  
Mechanical Earth Model

scholarly journals Static and dynamic effective stress coefficient of chalk

Geophysics ◽  
2012 ◽  
Vol 77 (2) ◽  
pp. L1-L11 ◽  
Author(s):  
M. Monzurul Alam ◽  
Ida Lykke Fabricius ◽  
Helle Foged Christensen
Keyword(s):  
Pore Pressure ◽  
Effective Stress ◽  
Mechanical Strain ◽  
Mechanical Tests ◽  
Differential Stress ◽  
Stress Regime ◽  
Hydrocarbon Reservoir ◽  
Stress Coefficient ◽  
The Difference ◽  
Stress Dependent

Deformation of a hydrocarbon reservoir can ideally be used to estimate the effective stress acting on it. The effective stress in the subsurface is the difference between the stress due to the weight of the sediment and a fraction (effective stress coefficient) of the pore pressure. The effective stress coefficient is thus relevant for studying reservoir deformation and for evaluating 4D seismic for the correct pore pressure prediction. The static effective stress coefficient [Formula: see text] is estimated from mechanical tests and is highly relevant for effective stress prediction because it is directly related to mechanical strain in the elastic stress regime. The corresponding dynamic effective stress coefficient [Formula: see text] is easy to estimate from density and velocity of acoustic (elastic) waves. We studied [Formula: see text] and [Formula: see text] of chalk from the reservoir zone of the Valhall field, North Sea, and found that [Formula: see text] and [Formula: see text] vary with differential stress (overburden stress-pore pressure). For Valhall reservoir chalk with 40% porosity, [Formula: see text] ranges between 0.98 and 0.85 and decreases by 10% if the differential stress is increased by 25 MPa. In contrast, for chalk with 15% porosity from the same reservoir, [Formula: see text] ranges between 0.85 and 0.70 and decreases by 5% due to a similar increase in differential stress. Our data indicate that [Formula: see text] measured from sonic velocity data falls in the same range as for [Formula: see text], and that [Formula: see text] is always below unity. Stress-dependent behavior of [Formula: see text] is similar (decrease with increasing differential stress) to that of [Formula: see text] during elastic deformation caused by pore pressure buildup, for example, during waterflooding. By contrast, during the increase in differential stress, as in the case of pore pressure depletion due to production, [Formula: see text] increases with stress while [Formula: see text] decreases.

scholarly journals Perforation location optimization through 1-D mechanical earth model for high-pressure deep formations

2021 ◽  
Author(s):  
Nagham Jasim Al-Ameri
Keyword(s):  
High Pressure ◽  
Young Modulus ◽  
Normal Pressure ◽  
Horizontal Stress ◽  
Earth Model ◽  
Location Selection ◽  
Geomechanical Properties ◽  
Well Production ◽  
The Difference ◽  
Mechanical Earth Model

AbstractOptimum perforation location selection is  an important study to improve well production and hence in the reservoir development process, especially for unconventional high-pressure formations such as the formations under study. Reservoir geomechanics is one of the key factors to find optimal perforation location. This study aims to detect optimum perforation location by investigating the changes in geomechanical properties and wellbore stress for high-pressure formations and studying the difference in different stress type behaviors between normal and abnormal formations. The calculations are achieved by building one-dimensional mechanical earth model using the data of four deep abnormal wells located in Southern Iraqi oil fields. The magnitude of different stress types and geomechanical properties was estimated from well-log data using the Techlog software. The directions of the horizontal stresses are determined in the current wells utilizing image-log formation micro-imager (FMI) and caliper logs. The results in terms of rock mechanical properties showed a reduction in Poisson’s ratio, Young modulus, and bulk modulus near the high-pressure zones as compared to normal pressure zones because of the presence of anhydrite, salt cycles, and shales. Low maximum and minimum horizontal stress values are also observed in high-pressure zones as compared to normal pressure zones indicating the effects of geomechanical properties on horizontal stress estimation. Around the wellbore of the studied wells, formation breakouts are the most expected situation according to the results of the wellbore stress state (effective vertical stress (σzz) > effective tangential stress (σθθ) > effective radial stress (σrr)).

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.

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.

Mudstone (“shale”) depositional and diagenetic processes: Implications for seismic analyses of source-rock reservoirs

2013 ◽  
Vol 1 (1) ◽  
pp. B7-B26 ◽  
Author(s):  
Bruce S. Hart ◽  
Joe H. S. Macquaker ◽  
Kevin G. Taylor
Keyword(s):  
Hydraulic Fracturing ◽  
Clay Minerals ◽  
Elastic Properties ◽  
Source Rock ◽  
Conceptual Models ◽  
Source Rocks ◽  
Geomechanical Properties ◽  
Fine Grained ◽  
Diagenetic Processes ◽  
Seismic Methods

Source-rock reservoirs are fine-grained petroleum source rocks (“shales” or “mudstones”) having geomechanical properties that allow those rocks to produce hydrocarbons at economic rates after stimulation by hydraulic fracturing. Many of the assumptions commonly adopted by geophysicists to characterize shales cannot be applied to source-rock reservoirs. For example, the mineralogies of many source-rock reservoirs are not dominated by clay minerals and so mathematical and/or conceptual models developed for clay-dominated mudstones are not appropriate and cannot be applied to them. Instead, mudstones of shale plays are generally dominated by biogenic calcite and/or quartz. We use terminology of sedimentary geology to show that anisotropy is scale-dependent in source-rock reservoirs, and we discuss the depositional and diagenetic processes that control these and other geophysical properties of interest. The mudstones of source-rock reservoirs may or may not be anisotropic at the lamination scale (i.e., millimeters), the scale commonly used to measure anisotropic parameters via core plugs, but they are nearly always anisotropic at the bedset (centimeters to several meters) and member (tens of meters) scales. Because of the anisotropic nature of mudstones, elastic properties are not scalars at the length/thickness scales that can be defined using seismic methods. Properties of interest are likely to be different parallel to bedding compared to perpendicular to bedding. Because of the subseismic scale of much of this variability, thin-bed effects are likely to influence the AVO behavior of source-rock reservoirs.

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