Sonic Scanner Helps in Identifying Reservoir Potential and Isotropic Characteristics of Khasib Formation

Abstract


Introduction
Accurate detection of reservoir permeability, naturally fractures distributed in the reservoir, and maximum stress orientation are essential parameters in reservoir evaluation and development.In general, these parameters are needed for accurate well placement, wellbore stability estimation, improved reserve estimation, and completion optimization.However, direct measurements of these properties are the most difficult stage in reservoir evaluation because these measurements can't be achieved for the total well depth or for all wells in the field.Conventional logging data such as resistivity and derived porosity from sonic or density log was used to evaluate reservoir fractures and permeability using specific models.When the used models are not accurate to estimate these properties, the results uncertainty are high.The development of sonic scanner tools allows for accurate determination of these properties as well as to provide continuous and direct measurements of them.Many techniques are used to evaluate permeability and detect fractures using sonic scanner tools (Brie et al., 1998;Pampuri et al., 1998).The proposed method in literatures used the Stoneley wave for fluid mobility estimation using Biot theory near the wellbore.The results of the proposed method were corrected for three parameters related to the invaded mud cake which are: mud slowness, mud attenuation, and pore fluid modulus (Brie et al., 1998).Pampuri et al. (1998), indicate the main advantage of permeability estimation using sonic scanner as compared to the estimated porosity using NMR method.Essam et al. (2009) in a case study for carbonate reservoir, used Stoneley wave tool for fracture characterization and hence for better reservoir evaluation.Dey, 2010 estimated reservoir permeability and fracture present using sonic scanner tools to increase coal gas reservoir productivity as a case study.Ghosh et al. (2010) used the estimated reservoir permeability within sonic scanner tools in swell-packer placements and segmented completion.Hajiyev et al. (2010) used sonic scanner tools and acoustic anisotropy information for stress direction detection that used for well placement detection and mud weight optimization.In his work, a case study is proposed for oil and gas condensate reservoirs using 3D formation acoustic properties from monopole, dipole, and Stoneley wave measurements.Kinoshita et al. (2016) proposed an approach for fracture analysis and anisotropic stress detection using dipole log designed for high angle inclined wells.Irawan et al. (2021) used integrated tools for fracture characterization in a case study for a carbonate tight reservoir, the tools used such as combining of high-resolution laterolog resistivity image (LWD) with multi-pole sonic (LWD).The proposed methodology involved identification of borehole breakouts, natural or drillinginduced fractures, faults and vugs from the high-resolution LWD image data for accurate fractures identification.Collins and Hornby (2017) estimated the borehole washout volume using Stoneley wave and other integrated tools from a case study well measurements such as borehole images and caliper log to identify fractures from bedding effects.
The reservoir under study (Khasib Formation) is an important reservoir in Halfaya oil field that is required accurate properties evaluation.The objective of this paper is to analyze the results of the Stoneley waves and Sonic Scanner log of real field data for accurate detection of reservoir mobility, fracture characterization, and maximum stress direction estimation of Khasib Formation.

Reservoir Properties and Lithological Description
Halfaya oil field in southeastern Iraq includes many reservoir accumulations.One of the main reservoirs in Halfaya oil field is Khasib Formation.The full stratigraphic description is shown in Fig. 1.The main petrophysical properties of this reservoir are illustrated in Fig. 2 after data interpretation using IP software.IP interpretation shows several log tracks such as Resistivity, Sonic, Neutron, water saturation, porosity, shale volume, Gamma ray, and the main lithological description of the studied interval (Petroleum Exploration Company, 2010).According to the changes in depositional cycles and formation lithology of Khasib Formation, the formation is divided into two main units KA and KB as shown in Fig. 2.Moreover, KA is subdivided into two subunits and KB is subdivided into three subunits.This reservoir is bounded from the top by Tanuma Formation and by Mishrif Formation from the bottom.
From Fig. 2, the main properties of this formation such as porosity, resistivity, and water saturation can be summarized to help in reservoir evaluation.It is observed that the unit KA1 has 16.06% average porosity, 29.64% average water saturation and 11.15 ohm.m average resistivity.While the unit KA2, has a range of 8.76% to 12.67% of average porosity, 45.63% to 83.62% of average water saturation, and 3.07 to 4.88 ohm.m of average resistivity.The properties of the unit KB range from 15.11% to 12.00% of average porosity, 24.69% to 48.89 of average water saturation, and 6.45 to 22.89 ohm.m of average resistivity.The average permeability of this reservoir is ranged from 0.13 to 1.46 md for unit KA, while the permeability range of unit KB is from 0.87 to 9.27 md.
The lithological description of this formation is mainly consisting of limestone, interbedded with claystone in the lower part of the Khasib A (KA) and Khasib B (KB).The limestone of KA represents about 97% of the total rock composition described as Light gray to medium gray, firm to moderately hard, subblocky to blocky, while the claystone represent 3% of the total rock composition described as light gray to grayish green, soft to firm, subblocky, slightly to moderately calcareous.The limestone in the KB layer represents 98% of the total formation composition described as Pale yellowish brown, light brown, moderate hard, and subblocky while the claystone represent 2% of total rock composition with green gray, firm to moderately hard, blocky, slightly calcareous, interbedded with nodular (Petroleum Exploration Company, 2010).

Sonic Scanner Tool
Sonic Scanner tool can provide an integrated analysis of formation acoustic properties.Formation properties characterization can be obtained through comprehensive analysis of the three broadband waveforms around the borehole such as Dipole, Monopole, and Stoneley wave.This analysis can be integrated using all other acquired data.The difference in obtaining compressional and shear slowness can be achieved by applying a wide range of transmitter-receiver distribution.When the transmitterreceiver distribution ranges from very short to very long spacing the compressional profile is obtained.While shear slowness profile are provide through inversions of the broadband dispersions of the dipole flexural and Stoneley modes (Qobi et al., 2001).The obtained wideband properties of radial shear slowness allow for additional measurements of formation slowness for both the neighboring and far formations.The new sonic tool design include 5 transmitters and 104 receivers allowing for higher signal to noise ratio and therefore the obtained slowness is determined with high accuracy.Fig. 3-A shows the recorded three types of waves including the arrival of compressional wave (P-wave) followed by shear wave (S-wave) and the late Stoneley wave.
In term of wave propagation in formation, both compressional and shear waves can be moved through the formations.While the Stoneley wave are surface wave that travels at the wellbore surface as illustrated in Fig. 3-B.The sonic scanner log was run in well X located in the studied field across the studied formations, using all the different sonic scanner operating modes.Each mode was recorded to extract the relevant information, associated with its specific applications and was acquired in combination with the conventional open hole logs.
The objective of Sonic Scanner data processing in current study was to extract the following reservoir information, using data from different modes: • Delta-T Compressional, Shear and Stoneley.
• Shear anisotropy determination from Sonic Scanner for Maximum Stress Direction • Permeability estimation from Sonic Scanner Stoneley.
• Fracture analysis from the Stoneley mode.
Since the Stoneley wave propagates as a piston-like compression of the borehole fluid in the borehole, when there are a permeable zones or a permeable fractures in the formation cause some energy losses.The difference in fracturese properties and permeable zones types affected the Stoneley waves in different ways.Many factors effect the Stonly borehole waves are mentioned by Brie et al. (1998) such as open fracture presents in hard rocks.In a vertical wells, Stonly borehole waves are affected by the low developed angle by the fractures while for a horizontal well Stonly waves are affected by the high fracture development.The high fractures orientation angle is an expected case for shale gas reservoirs.The Stonly borehole waves are also affected by the borehole rugosity and lithology changes; therefore, many corrections are necessary to control the quality of the measurements.

Shear Anisotropy Determination from Sonic Scanner for Maximum Stress Direction Estimation
In ideal situation (isotropic medium), sound waves travel with the same speed in the same formation type.In real situation, sound waves move in different speed and directions.This is due to different directions of alignment of stress within the same formation, as seen, in Fig. 4-A.Fractures presence and stresses distribution in formation are very affecting factors in shear wave's propagation.Shear waves can be divided into two components fast and slow shear with orthogonal polarization directions as detected by Sinha and Kostek (1996).This difference in sound waves speed and directions lead to wave propagation fastest in the stiffest rock direction and therefore introduce the phenomena of anisotropy.In general, two types of alignment horizontal and vertical introduce to two types of anisotropy.If the formation elastic properties vary vertically with depth without lateral variation, it is called transversally isotropic having vertical symmetric axis.Shear wave moves faster laterally along layers, than vertically due to anisotropy (Fig. 4-B).Detection of this anisotropy is useful for correlation purposes such that sonic with borehole seismic.If the elastic property varies horizontally with horizontal axis of symmetry, it is called transversally isotropic having horizontal symmetric axis.This phenomenon is common in the presence of fractures with vertical planes of weakness.In this case, shear waves traveling along fracture direction in competent rock travel faster than those traveling perpendicular to the fracture, as shown in Fig. 4-C.Four component rotation techniques are used in anisotropy analysis.These components are used to compute fast shear azimuth and rotated waveforms to fast and slow shear azimuth.The inputs of four component rotation for anisotropy analysis are raw waveforms from inline and cross-line measurements from XD dipole and YD dipole.The obtained waveforms from each dipole are utilized to determine the fast shear azimuth.While the direction and speed of both fast and slow shear wave are estimated mathematically using energy line concept.When a maximum energy is obtained from the rotated wave the induced angle is fast shear azimuth.If the waveform is estimated in the direction of fast shear azimuth, then the result is fast shear slowness.While slow shear is result if the waveform is perpendicular to fast shear azimuth.Anisotropy post processing computes slowness-based anisotropy and time-based anisotropy by the following equations.This is computed as the difference in the slowness or arrival time of the fast and slow shear waves, respectively, as follows: Where ANIDT is slowness-based anisotropy, ANIITT is time-based anisotropy, DTSlow is slow shear slowness, DTFast is fast shear slowness, TTDiff is arrival time difference between fast and slow shear waves, and TTFast is fast shear arrival time.
Four causes of anisotropy can be obtained from the dispersion behavior of the polarized waves as illustrated in Fig. 5.These cases are: Homogeneous Isotropic (HI) Model, shear slowness is the same in all directions.Inhomogeneous Isotropic Model, and shear slowness changes with distances from the borehole.Based on the dispersion plots, fast and slow shear curves will overlay and be higher than the HI model at higher frequencies.
Homogeneous Anisotropic Formation Model: Fast and slow shear are parallel to each other.
Inhomogeneous Anisotropic Formation Model: Shear velocity is a function of radius and angle, with the slowest shear velocity in the direction of minimum stress.On a dispersion plot, this is characterized as a crossover of the fast and slow shear as frequency increases.

Permeability Estimation from Sonic Scanner Stoneley Wave
The Stoneley wave is bounded waves that can be propagating between solid and a fluid medium.In its low frequency mode, the sonic scanner monopole generates Stoneley wave in the boreholes and at these frequencies the Stoneley mode becomes a tube wave.The Stoneley wave can be thought of as a pressure pulse that travels along the borehole wall, with its velocity depending on the interaction between the formation and the borehole fluid.Stoneley wave slows down and is attenuated when passing a porous media due to fluid movement in the formation controlled by the hydraulic effect of the Stoneley pulse.Generally, the parameter measured by the Stoneley wave is the fluid mobility or the ratio of permeability to fluid viscosity.An intrinsic permeability can be determined from the fluid mobility using fluid viscosity and relative permeability curves (Tang et al., 1991).
The Stoneley fluid mobility estimation was carried in current study based on the Biot poro-elastic model.This model incorporates the shear modulus of the formation, Mud cake impedance, and fluid compressibility of the pore fluid sand an estimate of the stiffness of the mud cake membrane.The equation describing this relationship is outlined below: Where KB is borehole fluid bulk modulus, Shmod is formation Shear Modulus, Rhof is borehole fluid density, Freq is angular frequency, Ra is borehole radius, and Z is mud cake impedance

Fracture Analysis from Sonic Scanner Stoneley Reflection
The borehole Stoneley wave is sensitive to open fractures.The effect of the tube wave passing an open fracture creates an energy pulse into the high permeable streak and resulting in an energy reflection that travels up and down the borehole and appears as chevron patterns on the Stoneley waveform as shown in Fig. 6.Evaluating the waveform in the frequency domain where the reflection energy is borehole compensated separates the transmitted and reflected Stoneley waves.The energy of reflection and transmission is related to the fracture aperture, where the stronger the reflection the greater the fracture permeability.The reflections are also caused by the boundary at hole washouts and changes in acoustic impedance at major lithology and porosity interfaces.

Sonic Scanner Results and analysis for Khasib Formation
Sonic scanner tool results analysis obtained from (IP) are summarized in Fig. 7.This figure shows the Sonic scanner compressional (P), shear (S), and Stoneley wave energy of the interested Khasib Formation for the well X.These obtained data are very useful to obtain reservoir properties using equations 1 to 3.
The high quality waveform obtained results from sonic scanner log allow for clear characteristics of a typical formation.Even formation properties at different directions can be identified using sonic scanner data.This is called acoustic anisotropy data, its high sensitivity to direction changes comes from the improved signal to noise ratio data recorded.Fig. 7 illustrates the obtained sonic scanner log for well X through Khasib Formation.For the reservoir under study, the sonic scanner tool analysis is used to characterize reservoir properties in term of maximum stress detection, permeability estimation, and fracture detection as illustrated in the following sections.In general, Fig. 8 shows that there are two intervals that show anisotropy in this well through the interested formation which are: Interval D from 2565 to 2829 m depth and interval E from 2829 to 3342 m depth.For interval D the difference between maximum and minimum energy (track-1) and DT (track-4) shows some anisotropy in this section.The dispersion plots seem to suggest the formation in this interval is inhomogeneous anisotropic in some intervals and isotropic in some intervals.Dispersion analysis shows presence of inhomogeneous anisotropy formation at depths 2572.9 m and homogeneous isotropy at depth 2716.8 m.For interval E (2829 -3342m) the difference between maximum and minimum energy (track-1), DT based and time anisotropy (track-4) shows anisotropy in this section.The dispersion plots demonstrate some inhomogeneous anisotropy.Dispersion analysis suggests presence of stress induced anisotropy at the depth 2847.4 m.This founding agree with previous studt results for the same formation (Al-Ameri, 2015).
The Stoneley fluid mobility estimation was carried in the current study based on the Biot poroelastic model as shown in Fig. 9.The far monopole low frequency (Stoneley) mode is acquired at low frequency and over a sufficiently wide frequency range.In the absence of any formation tester or well test data for several intervals, Stoneley mobility is the only direct measurement available for mobility evaluation.In some intervals in Khasib Formation such as from 2980 to 3030 m Stoneley mobility varies from 1-100 md/cp.Also, in the zone of large washouts like 3120 m and 3265 m, high unreliable mobility shoot up can be seen.The accuracy of this technique in obtaining reservoir permeability was compared to core data derived permeability at several depths as shown in Fig. 10 (red dots for core data).The comparison results show accepted obtained permeability from Stoneley wave within 7% average difference of the measured core data.
In term of fracture detection, there are two waveforms presented in the last track of Fig.

Conclusions
Sonic Scanner logging, using Stoneley, monopole compressive (P) and shear (S) mode were combined for well X through Khasib Formations.In-situ stress direction, fluid mobility at the borehole was determined to assist in evaluating reservoir potential.The dipole shear anisotropy analysis indicated the presence of some anisotropy across several intervals of Khasib Formations.The average direction of the maximum horizontal stress in this formation is NW10 to N16E in well X.The fluid mobility derived from the Sonic Scanner Stoneley provides the mobility range varies from of 1-100 md for this formation.The obtained data has been calibrated with respect to the measured core data available at certain depths of this formation.Sonic Scanner Stoneley fracture analysis indicated no apparent fracture in depths of the borehole that is affected by washouts in the formation and also due to presence of many lithological layers.It is also worth noting that the presence of all of the Cheveron patterns seen in Stoneley waveforms is the result of wash outs and presence of layers in the borehole.Freq: angular frequency.
Z: mud cake impedance, in.

Fig. 7 .
Fig. 7. Sonic scanner (P, S, and Stoneley) wave energy of Khasib Formation for the well X.

Fig. 8
Fig. 8 illustrates the anisotropy computation in the Khasib Formation in the well X.The difference between the minimum and maximum cross component shear energy shown in depth track is an indicator of anisotropy (green shaded).The tool orientation (blue) shown in track 2 is used to determine the absolute fast shear azimuthal direction (red) with its uncertainty (gray shaded) track 3. Acoustic time
10. Waveform created by model waves and the actual waveform is presented in the last track.Fracture analysis is done in the present work using low frequency Stoneley reflection analysis.The inversion of reflection coefficients were performed to solve for existing fractures.Based on Tezuka et al 1997 model, waveforms were generated from the formation compressional, shear, stoneley, density and caliper response.The modeled reflections were computed to illustrate the borehole irregularity response of the Stoneley wave.Chevron pattern on waveform of the Stoneley waveforms in the absence of the same patterns on the modeled waveforms is the indication of possible open fractures.Whereas Chevron patterns generated due to bed boundaries and borehole rugosity will be reflected in the current borehole, no fracture is detected by Stoneley fracture analysis in the main reservoir zones.The cheveron pattern is mainly caused by the borehole washouts and changing in lithology.As illustrated in the Fig. 8 shown below, borehole is highly washed out and no major fracture patterns have been observed from the Stoneley fracture analysis.