Estimation of the current stress field and fault reactivation analysis in the Asmari reservoir, SW Iran

Taghipour, Majid; Ghafoori, Mohammad; Lashkaripour, Gholam Reza; Moghaddas, Nasser Hafezi; Molaghab, Abdullah

doi:10.1007/s12182-019-0331-9

Cited by 26 publications

(7 citation statements)

References 40 publications

(62 reference statements)

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“…These results are similar to those reported by Yaghoubi and Zeinali [17] for the Cheshmeh-khosh field, Haghi, Chalaturnyk and Ghobadi [18] for the Ahvaz field in the southern part of the Dezful Embayment, and others [58,68]. Their results show that normal/strike-slip faulting predominates in the sedimentary cover to a depth of 5 km.…”

Section: Stress Magnitudesupporting

confidence: 90%

Seismicity and the State of Stress in the Dezful Embayment, Zagros Fold and Thrust Belt

et al. 2021

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This study focuses on determining the orientation and constraining the magnitude of present-day stresses in the Dezful Embayment in Iran’s Zagros Fold and Thrust Belt. Two datasets are used: the first includes petrophysical data from 25 wells (3 to 4 km deep), and the second contains 108 earthquake focal mechanisms, mostly occurring in blind active basement faults (5 to 20 km deep). Formal stress inversion analysis of the focal mechanisms demonstrates that there is currently a compressional stress state ( in the basement. The seismologically determined SHmax direction is 37° ± 10°, nearly perpendicular to the strike of most faults in the region. However, borehole geomechanics analysis using rock strength and drilling evidence leads to the counterintuitive result that the shallow state of stress is a normal/strike-slip regime. These results are consistent with the low seismicity level in the sedimentary cover in the Dezful Embayment, and may be evidence of stress decoupling due to the existence of salt layers. The stress state situation in the field was used to identify the optimally oriented fault planes and the fault friction coefficient. This finding also aligns with the prediction Coulomb faulting theory in that the N-S strike-slip basement Kazerun Fault System has an unfavorable orientation for slip in a reverse fault regime with an average SW-NE SHmax orientation. These results are useful for determining the origin of seismic activity in the basin and better assessing fault-associated seismic hazards in the area.

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Section: Stress Magnitudesupporting

confidence: 90%

Seismicity and the State of Stress in the Dezful Embayment, Zagros Fold and Thrust Belt

et al. 2021

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“…The horizontal stresses can be anywhere in the triangles, indicating a specific stress regime (i.e., normal, reverse and strike-slip). The following formulations are needed to build the stress polygon [Taghipour et al, 2019]:…”

Section: Young and Maloney [2015]mentioning

confidence: 99%

“…The actual stimulation pressure may be less than the value estimated based on the aforementioned equation due to, among other features, the presence of pre-existing natural fractures. Thus, the critical fluid pressure required to induce slip on an optimally oriented fracture considering a friction coefficient of 0.6 was estimated as [e.g., Rutqvist et al, 2007, Taghipour et al, 2019:…”

Section: Effective Stimulation Pressurementioning

confidence: 99%

Estimating theoretical stress regime for engineered geothermal energy systems in an arctic community (Kuujjuaq, Canada)

Miranda¹,

Raymond²,

Dezayes³

2023

Comptes Rendus. Géoscience

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In remote northern regions, lacking deep geothermal exploratory boreholes, a theoretical approach to provide a first-order estimate of the stress regime seems a useful tool. Literature data was used in this context to evaluate the orientation of the stress components and empirical relationships were applied to calculate their magnitude in a community of Nunavik, northern Quebec. A Monte Carlo-based sensitivity analysis was carried out due to the uncertainty of the input parameters. Mohr-Coulomb friction and slip tendency analyses were additionally undertaken to assess the stress state and potential reactivation of existing fractures. The results highlight how the poor knowledge of the stress field has an important impact on the design and development of engineered geothermal energy systems in the Canadian off-grid community of Kuujjuaq.

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“…Reservoir geomechanical characterization is crucial in achieving stable wellbore, perforation direction, stimulation and completion schemes, which greatly impacts reservoir production (Blanton and Olson 1999;Zoback 2007;Sen et al 2019;Taghipour et al 2019;Baouche et al 2022;Radwan and Sen 2021a, b). The sedimentary basins for petroleum accumulations are subjected to in situ stresses which are mainly related to their geological tectonic setting.…”

Section: Introductionmentioning

confidence: 99%

Implications of machine learning on geomechanical characterization and sand management: a case study from Hilal field, Gulf of Suez, Egypt

Abdelghany

Hammed

Radwan

et al. 2022

J Petrol Explor Prod Technol

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Sand production is one of the major challenges in the oil and gas industry, so a comprehensive geomechanical analysis is necessary to mitigate sand production in mature fields. As the pore pressure drastically decline in depleted reservoirs, the sand production risk becomes more critical and needs to be studied. However, the absence of key logs in many wells is a big challenge in the petroleum industry, and most geologists and engineers use empirical equations to predict missed log intervals. We conducted a comprehensive geomechanical modeling study on a full set of logs from two wells from the Hilal field, Gulf of Suez, Egypt, to infer the geomechanical elements and predict sand production. We have used the multi-arm calipers to calculate the actual depth of damage ratio to validate the geomechanical parameters in the prognosis model and confirm the stress orientations. We used machine learning approach to infer key sonic log in X-10 well to replace the empirical equations. The multi-arm calipers analysis showed an observed anisotropy in the hole diameter size with more enlargement in the ENE direction and fits with the minimum horizontal stress direction in the direction of N 60oE. The later also deduced the maximum horizontal stress direction in N150 ° based on the induced fractures from borehole image data in a nearby field. We developed and compared two sand management models: one using empirical equation and the other using machine learning. The model driven by the Gardner equation suggests sand production from day one, which is not matched with the production data, while the model driven by machine learning suggests no sand production risk, which is matched with the actual production data. Our results demonstrate the advantage of using machine learning technique in geomechanical studies on the classical empirical equations in the area of study that can be applied in other basins. The findings of this study can help with a better understanding of the implications of machine learning on geomechanical characterization and sand management.

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Estimation of the current stress field and fault reactivation analysis in the Asmari reservoir, SW Iran

Cited by 26 publications

References 40 publications

Seismicity and the State of Stress in the Dezful Embayment, Zagros Fold and Thrust Belt

Seismicity and the State of Stress in the Dezful Embayment, Zagros Fold and Thrust Belt

Estimating theoretical stress regime for engineered geothermal energy systems in an arctic community (Kuujjuaq, Canada)

Implications of machine learning on geomechanical characterization and sand management: a case study from Hilal field, Gulf of Suez, Egypt

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