Identification of Drilling Efficiency Using Log-Derived Cation Exchange Capacity in Shale Formation

Shale and shaly formations constitute about 70% to 80% of the total rock formations drilled worldwide, and the most of footage drilled in gas and oil wells is in shale and shaly rocks. Drilling in shale sections in many cases causes wellbore instability and slow drilling problems. In this study, cation exchange capacity of shale is estimated using a relatively simple petrophysical model. The validation of this model is achieved with experimental values of cation exchange capacity. The estimation of cation exchange capacity by this model and common logs data has exhibited potentiality for distinguishing effective/ineffective drilling in shale formations. Drilling and petrophysical data gathered at controlled condition is required in order to optimize the proposed technique. Have knowledge of properties and location of shales permits for remedial actions in future offset well or while drilling in case of logging while drilling (LWD) is used.


Introduction:
Optimization of drilling rate plays an important role in reducing of drilling operation expense [1]. Slow drilling/bit balling problem was considered as one of the main causes of ineffective bit performance in case of drilling shale section using water-based mud [2]. The cohesion between shale drill cuttings results in occurring of this problem. Bit efficiency is reduced because of the cuttings agglomeration lead to create a ball. This ball in turn, leads to jam the space between the body of bit and hole-bottom [3].
When the required time for drilling a well increases, the expense is already increases. Furthermore, the rate of penetration (ROP) decreases with increasing of depth in drilling of shale formations [4,5]. Oil and gas industry gives a lot of attention for drilling in the shale formations due to the remedial practice to pass the problems experienced in such formations is by using oil-based mud and polycrystalline diamond compact, PDC, bits. Using a novel inhibitive drilling fluid to reduce the interaction between the water-based mud and sensitive shale rock is considered one of the main keys to performing aims of high levels of wellbore stability, minimize dilution rate, bit balling problem, hole gauge and enhanced economics of drilling operation. Unfortunately, using of a lot of these water-based muds has not prevented the incidents of bit balling and cuttings accretion, in turn will cause in lost time and reducing of drilling rate [12]. Therefore, using these muds for drilling shale formations is not always potential or suitable.
The alternative way in such condition is by using water-based mud and PDC bits [5]. However, the effectiveness of this way has appeared less than the use of oilbased mud with PDC bits. If using water-based mud with PDC bits can be resulted inefficient drilling performance, the expense can be decreased significantly.
Development of drilling performance is one of the main aspects of this study. The slow drilling problem has been investigated by many researchers. Demircan G., Smith J.R and Bassiouni Z. (2000) [3] stated that the low ROP in shale formations was related to CEC calculated from log data. They presented a reasonable relationship between the ROP and CEC as helpful mean in diagnosing of drilling performance. Abdolhamid S. and Ali C. (2018) [13] developed a model by correlating the CEC values of the shaly formation with drilling parameters. They mentioned that CEC values of shale formation cannot be directly and continuously measured. Usually, CEC values can be obtained from laboratory or by using empirical relationships from well logs. But, by taking advantage of the logs-derived, using correlations is a beneficial way. They presented a graphical correlation which utilized the drilling parameters and CEC values in order to provide a tool for the prediction of drilling class. Therefore, establishing a method to relate the drilling performance in shale formations with their properties is the main purpose in this study. This proposed method will give the drilling crew an indication of effective or ineffective drilling at given time. Consequently, it will help the drilling crew to choose the corrective actions to increase the ROP in order to decrease the drilling expenses. In other ward, it is capable of driller to detect the drilling rate and to preserve it at efficient level.

Data preparation
Field data (drilling and well logs data of well GR-130 and G-38) was obtained from shale formation in a southern Iraqi oilfield used to exemplify of this problem in this study. The all necessary petrophysical and drilling data is available for well G-130 and G-38. Fundamental drilling parameter available of wells involve rate of penetration (ROP), rotary speed (RPM), weight on bit (WOB), hydraulic data, and torque. The needed petrophysical data include gamma ray, resistivity logs, neutron and density porosity logs are also available.

Geological background of studied Field
An Iraqi oilfield is situated in southern of Iraq in Thi-Qar governorate about (85 km) to the north of Nassiriyah city Figure (1) [14]. It was discovered in 1984. The field's structure is (10 km) width and (31 km) length, gently dipping low relief anticline with a trend extends in North-West to South-East direction [14] [15]. It has proven by exploration and appraisals wells, that it has a hydrocarbon accumulation

Petrophysical model of CEC Estimation:
Considerably, the clay type influence on drilling efficiency, a petrophysical model was applied to relate cation exchange capacity (CEC) with shale characteristics commonly estimated using logs technique, applicable petrophysical data with drilling date lead to present an application for potential drilling optimization.
Waxman-Smits shaly sand model is considered as parallel bound water and far water conductivity equation which is presented as following [6]: [ ] Where: R: is the resistivity of the water bearing shaly sand, ohm-m. F * : is the formation factor of the shaly sand.
R w : is the resistivity of the far water, ohm-m.
B: is the equivalent counterion conductance, mho/m (meq/cc), and Q v : is the counterion concentration, meq /cc pore volume.
Using the perfect shale concept, which assumes that all the electric conductivity is due to bound water [7], the above equation reduces to: Where: F sh and R sh are the shale formation resistivity factor and resistivity respectively. B max is the maximum equivalent counterion conductance.
Solving for Q yields: is related to cation exchange capacity by [8]: Where: : Total porosity, fraction.
: is the density of rock matrix containing shale, g/cc, and CEC: is the cation exchange capacity, meq/100 gm. T: is the temperature of zone of interest, .
Dual water model [10], the total porosity is calculated as an average of the density and neutron porosity i.e.: The shale formation factor is then calculated by [10]: F sh = …….. (7) Figure (3) and (4) illustrates the results of the log-derived CEC with depth for well G-130 and G-38 respectively.

Experimental Measurements of CEC:
The cation exchange capacity (CEC) measurements were accomplished on drill cuttings samples only available for well G-130.
The cation exchange capacity values were measured using blue methylene test for the available drill cutting samples which were taken for the interval 2560 to 2567 m of well G-130, and the results are shown in Table (

Normalized Rate of Penetration (ROPn):
The ROP normalization is has to be achieved in order to combine and compare data from various drilled intervals and drilled wells. The following model is used to normalize the ROP [11]: Where; : Rate of penetration, fph.
: Normalized rate of penetration.

Correlation of with Log-Derived CEC:
Figures (6)