Improved Pore-Pressure Prediction and Mechanical Earth Model Estimation Through Binary Decomposition of Seismic Inversion Data in Subresolution Clastic Sequences

2004 ◽  
Author(s):  
Folke Engelmark
2003 ◽  
Author(s):  
P. M. Doyen ◽  
A. Malinverno ◽  
R. Prioul ◽  
P. Hooyman ◽  
S. Noeth ◽  
...  

2021 ◽  
Vol 8 ◽  
pp. 55-79
Author(s):  
E. Bakhshi ◽  
A. Shahrabadi ◽  
N. Golsanami ◽  
Sh. Seyedsajadi ◽  
X. Liu ◽  
...  

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.  


2021 ◽  
Author(s):  
Jose Francisco Consuegra

Abstract Accurate pore pressure prediction is required to determine reliable static mud weights and circulating pressures, necessary to mitigate the risk of influx, blowouts and borehole instability. To accurately estimate the pore pressure, the over-pressure mechanism has to be identified with respect to the geological environment. One of the most widely used methods for pore pressure prediction is based on Normal Compaction Trend Analysis, where the difference between a ‘normal trend' and log value of a porosity indicator log such as sonic or resistivity is used to estimate the pore pressure. This method is biased towards shales, which typically exhibit a strong relationship between porosity and depth. Overpressure in non-shale formations has to be estimated using a different method to avoid errors while predicting the pore pressure. In this study, a different method for pore pressure prediction has been performed by using the lateral transfer approach. Many offset wells were used to predict the pore pressure. Lateral transfer in the sand body was identified as the mechanism for overpressure. This form of overpressure cannot be identified by well logs, which makes the pore pressure prediction more complex. Building a 2D geomechanical model, using seismic data as an input and following an analysis methodology that considered three type of formation fluids - gas, oil and water in the sand body, all pore pressure gradients related to lateral transfer for the respective fluids were evaluated. This methodology was applied to a conventional reservoir in a field in Colombia and was helpful to select the appropriate mud weight and circulating pressure to mitigate drilling risks associated to this mechanism of overpressure. Seismic data was critical to identifying this type of overpressure mechanism and was one of the main inputs for building the geomechanical earth model. This methodology enables drilling engineers and geoscientists to confidently predict, assess and mitigate the risks posed by overpressure in non-shale formations where lateral transfer is the driving mechanism of overpressure. This will ensure a robust well plan and minimize drilling/well control hazards associated with this mode of overpressure.


AAPG Bulletin ◽  
2018 ◽  
Vol 102 (04) ◽  
pp. 691-708 ◽  
Author(s):  
Fausto Mosca ◽  
Thomas Hantschel ◽  
Obren Djordjevic ◽  
Jim McCarthy ◽  
Ana Krueger ◽  
...  

2010 ◽  
Author(s):  
Hamid R. Soleymani ◽  
SeyedMohsen SeyedAli ◽  
Mohammad A. Riahi

2004 ◽  
Vol 23 (1) ◽  
pp. 52-59 ◽  
Author(s):  
Jorge L. López ◽  
Penne M. Rappold ◽  
Gustavo A. Ugueto ◽  
James B. Wieseneck ◽  
Cung K. Vu

2019 ◽  
Vol 59 (2) ◽  
pp. 856
Author(s):  
Peter G. Boothby ◽  
Ratih Puspitasari ◽  
Sanjay Thakur ◽  
Zachariah John Pallikathekathil ◽  
Chris Walton

Understanding the influence of geomechanics early in the field development phase facilitates reservoir management planning. To capture complex geology and associated field development, a 3D mechanical earth model (3D MEM) with finite element method (FEM) approach was selected to analyse the geomechanical-related risks associated with two fields in the North West Shelf, Australia. The 3D MEMs were constructed using geological static models, and seismic-derived horizons and faults. The 3D properties were propagated based on core-calibrated 1D properties and controlled by stratigraphy, 3D facies and seismic inversion volumes. The FEM was used to calculate the equilibrium of stresses and strains within the 3D MEMs. The 3D properties and pre-production stresses were validated in blind test wells before forward modelling. The 3D MEMs were linked to the dynamic reservoir models to capture the pressure evolution throughout the field lifecycle. The results were used to analyse the risks associated with compaction, subsidence, fault instability, completion integrity and drilling stability of infill wells through depleted reservoirs. The results provided insight in managing the risk early in field development stage. The study’s largest challenge was integrating a large volume of data to ensure that the structural complexity and rock heterogeneity were captured and consistent with the geological understanding of the field. A multi-disciplinary team of earth scientists and reservoir and geomechanics engineers worked together, and the value of data integration, good communication and teamwork were key success factors. Lessons learned and best practices were captured throughout the study and provided valuable feedback for future works.


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