Fracture Azimuth—A Shallow Experiment

1980 ◽  
Vol 102 (2) ◽  
pp. 99-105 ◽  
Author(s):  
M. B. Smith ◽  
J. M. Logan ◽  
M. D. Wood

A small-scale, shallow experiment was conducted by Amoco Production Research, Sandia Laboratories, and the U. S. Geological Survey, in order to study the potential of several geophysical monitoring techniques for determining in-situ fracture geometry. The program included core analysis, surface strain gage over-coring, borehole measurements, tiltmeter surveys, surface electric potential measurements, and post-coring. Each of the techniques correctly measured an East-West fracture which was longer to the East. This azimuth was apparently controlled by in-situ stresses, and it was noted that these were not affected by a horizontal stress relief located due East of the site.

2021 ◽  
Author(s):  
Jianguo Zhang ◽  
Karthik Mahadev ◽  
Stephen Edwards ◽  
Alan Rodgerson

Abstract Maximum horizontal stress (SH) and stress path (change of SH and minimum horizontal stress with depletion) are the two most difficult parameters to define for an oilfield geomechanical model. Understanding these in-situ stresses is critical to the success of operations and development, especially when production is underway, and the reservoir depletion begins. This paper introduces a method to define them through the analysis of actual minifrac data. Field examples of applications on minifrac failure analysis and operational pressure prediction are also presented. It is commonly accepted that one of the best methods to determine the minimum horizontal stress (Sh) is the use of pressure fall-off analysis of a minifrac test. Unlike Sh, the magnitude of SH cannot be measured directly. Instead it is back calculated by using fracture initiation pressure (FIP) and Sh derived from minifrac data. After non-depleted Sh and SH are defined, their apparent Poisson's Ratios (APR) are calculated using the Eaton equation. These APRs define Sh and SH in virgin sand to encapsulate all other factors that influence in-situ stresses such as tectonic, thermal, osmotic and poro-elastic effects. These values can then be used to estimate stress path through interpretation of additional minifrac data derived from a depleted sand. A geomechanical model is developed based on APRs and stress paths to predict minifrac operation pressures. Three cases are included to show that the margin of error for FIP and fracture closure pressure (FCP) is less than 2%, fracture breakdown pressure (FBP) less than 4%. Two field cases in deep-water wells in the Gulf of Mexico show that the reduction of SH with depletion is lower than that for Sh.


Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yushuai Zhang ◽  
Shangxian Yin ◽  
Jincai Zhang

Methods for determining in situ stresses are reviewed, and a new approach is proposed for a better prediction of the in situ stresses. For theoretically calculating horizontal stresses, horizontal strains are needed; however, these strains are very difficult to be obtained. Alternative methods are presented in this paper to allow an easier way for determining horizontal stresses. The uniaxial strain method is oversimplified for the minimum horizontal stress determination; however, it is the lower bound minimum horizontal stress. Based on this concept, a modified stress polygon method is proposed to obtain the minimum and maximum horizontal stresses. This new stress polygon is easier to implement and is more accurate to determine in situ stresses by narrowing the area of the conventional stress polygon when drilling-induced tensile fracture and wellbore breakout data are available. Using the generalized Hooke’s law and coupling pore pressure and in situ stresses, a new method for estimating the maximum horizontal stress is proposed. Combined it to the stress polygon method, a reliable in situ stress estimation can be obtained. The field measurement method, such as minifrac test, is also analyzed in different stress regimes to determine horizontal stress magnitudes and calibrate the proposed theoretical method. The proposed workflow combined theoretical methods to field measurements provides an integrated approach for horizontal stress estimation.


2021 ◽  
Vol 19 (3) ◽  
pp. 45-44
Author(s):  
Homa Viola Akaha-Tse ◽  
Michael Oti ◽  
Selegha Abrakasa ◽  
Charles Ugwu Ugwueze

This study was carried out to determine the rock mechanical properties relevant for hydrocarbon exploration and production by hydraulic  fracturing of organic rich shale formations in Anambra basin. Shale samples and wireline logs were analysed to determine the petrophysical, elastic, strength and in-situ properties necessary for the design of a hydraulic fracturing programme for the exploitation of the shales. The results obtained indicated shale failure in shear and barreling under triaxial test conditions. The average effective porosity of 0.06 and permeability of the order of 10-1 to 101 millidarcies showed the imperative for induced fracturing to assure fluid flow. Average Young’s modulus and Poisson’s ratio of about 2.06 and 0.20 respectively imply that the rocks are favourable for the formation and propagation of fractures during hydraulic fracking. The minimum horizontal stress, which determines the direction of formation and growth of artificially induced hydraulic fractures varies from wellto-well, averaging between 6802.62 to 32790.58 psi. The order of variation of the in-situ stresses is maximum horizontal stress>vertical stress>minimum horizontal stress which implies a reverse fault fracture regime. The study predicts that the sweet spots for the exploration and development of the shale-gas are those sections of the shale formations that exhibit high Young’s modulus, low Poisson’s ratio, and high brittleness. The in-situ stresses required for artificially induced fractures which provide pore space for shale gas accumulation and expulsion are adequate. The shales possess suitable mechanical properties to fracture during hydraulic fracturing. Application of these results will enhance the potentials of the onshore Anambra basin as a reliable component in increasing Nigeria’s gas reserves, for the improvement of the nation’s economy and energy security. Key Words: Hydraulic Fracturing, Organic-rich Shales, Rock Mechanical Properties, Petrophysical Properties, Anambra Basin


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ahmed Farid Ibrahim ◽  
Ahmed Gowida ◽  
Abdulwahab Ali ◽  
Salaheldin Elkatatny

AbstractDetermination of in-situ stresses is essential for subsurface planning and modeling, such as horizontal well planning and hydraulic fracture design. In-situ stresses consist of overburden stress (σv), minimum (σh), and maximum (σH) horizontal stresses. The σh and σH are difficult to determine, whereas the overburden stress can be determined directly from the density logs. The σh and σH can be estimated either from borehole injection tests or theoretical finite elements methods. However, these methods are complex, expensive, or need unavailable tectonic stress data. This study aims to apply different machine learning (ML) techniques, specifically, random forest (RF), functional network (FN), and adaptive neuro-fuzzy inference system (ANFIS), to predict the σh and σH using well-log data. The logging data includes gamma-ray (GR) log, formation bulk density (RHOB) log, compressional (DTC), and shear (DTS) wave transit-time log. A dataset of 2307 points from two wells (Well-1 and Well-2) was used to build the different ML models. The Well-1 data was used in training and testing the models, and the Well-2 data was used to validate the developed models. The obtained results show the capability of the three ML models to predict accurately the σh and σH using the well-log data. Comparing the results of RF, ANFIS, and FN models for minimum horizontal stress prediction showed that ANFIS outperforms the other two models with a correlation coefficient (R) for the validation dataset of 0.96 compared to 0.91 and 0.88 for RF, and FN, respectively. The three models showed similar results for predicting maximum horizontal stress with R values higher than 0.98 and an average absolute percentage error (AAPE) less than 0.3%. a20 index for the actual versus the predicted data showed that the three ML techniques were able to predict the horizontal stresses with a deviation less than 20% from the actual data. For the validation dataset, the RF, ANFIS, and FN models were able to capture all changes in the σh and σH trends with depth and accurately predict the σh and σH values. The outcomes of this study confirm the robust capability of ML to predict σh and σH from readily available logging data with no need for additional costs or site investigation.


Author(s):  
D.M. Seyedi ◽  
C. Plúa ◽  
M. Vitel ◽  
G. Armand ◽  
J. Rutqvist ◽  
...  

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