Tariq, Zeeshan (King Fahd University of Petroleum & Minerals) | Mahmoud, Mohamed (King Fahd University of Petroleum & Minerals) | Abdulraheem, Abdulazeez (King Fahd University of Petroleum & Minerals)
Carbonate rocks have a very complex pore system due to the presence of interparticle and intra-particle porosities. This makes the acquisition and analysis of the petrophysical data, and the characterization of carbonate rocks a big challenge. In this study, functional network tool is used to develop a model to predict water saturation using petrophysical well logs as input data and the dean-stark measured water saturation as an output parameter. The data comprised of more than 200 well log points corresponding to available core data. The developed FN model was optimized by using several optimization algorithms such as differential evolution (DE), particle swarm optimization (PSO), and covariance matrix adaptation evolution strategy (CMAES). FN model optimized with PSO found to be the most robust artificial intelligence (AI) model to predict water saturation in carbonate rocks. The results showed that the proposed model predicted the water saturation with an accuracy of 97% when related to the experimental core values. In this study in addition to the development of optimized FN model, an explicit empirical correlation is also extracted from the optimized FN model. To validate the proposed correlation, three most commonly applied water saturation models (Simandoux, Bardon and Pied model, Fertl and Hammack Model, Waxman-Smits, and Indonesian) from literature were selected and subjected to same well log data as the AI model to estimate water saturation. The estimated water saturation values for AI and other saturation models were then compared with experimental values of testing data and the results showed that AI model was able to predict water saturation with an error of less than 5% while the saturation models did the same with lesser accuracy of error up to 50%. This work clearly shows that computer-based machine learning techniques can determine water saturation with a high precision and the developed correlation works extremely well in prediction mode.
Abdelgawad, Khaled (King Fahd University of Petroleum & Minerals) | Mahmoud, Mohamed (King Fahd University of Petroleum & Minerals) | Elkatatny, Salaheldin (King Fahd University of Petroleum & Minerals) | Patil, Shirish (King Fahd University of Petroleum & Minerals)
Barium Sulfate (Barite) is one of the common oil and gas field scales formed inside the production equipment and in the reservoir. Barite is also a common weighting material used during drilling oil and gas wells. Barium sulfate scale may exist as well in carbonate formations. The removal of barium sulfate from calcium carbonate formation is a challenging problem because of the solubility of calcium carbonate is higher compared to that of barium sulfate in different acids. In addition, barium sulfate is not soluble in the regular acids such as hydrochloric (HCl) acid and other organic acids.
In this paper, the effect of calcium carbonate on barium sulfate solubility in a chelating agent and converter catalyst was investigated using solubility experiments at 80°C as a function of time. 20 wt.% DTPA with 6 wt.% potassium carbonate (converter) were used at pH of 12. The effect of calcium chelation on the barium sulfate solubility was studied in two scenarios. The first scenario when Barium sulfate is dissolved first then the solution reacts with calcium carbonate. The second scenario when both calcium carbonate and barium sulfate are exposed to the DTPA solution at the same time. In addition, the effect of calcium carbonate loading on the barium sulfate solubility was determined using 25, 50, 75, and 100 wt.% of the scale as calcium carbonate. As an evaluation criterion, inductively coupled plasma (ICP) was used to analyze the cation concentration and determine the solubility of each scale type.
For the two scenarios of barium sulfate dissolution, the presence of calcium carbonate had a significant effect on the solubility of barium sulfate. When DTPA solution got saturated first with barium cations after 24 hours, and the addition of calcium carbonate to the solution will cause immediate barium drop of solution (concentration drop from 2140 to 1984 ppm in 30 min in 50 ml solution) which cause precipitation of barium sulfate. In addition, simultaneous chelation of both calcium carbonate and barium sulfate showed a low barium sulfate solubility compared to calcium carbonate. This can be explained by the high affinity of DTPA to calcium compared to barium.
It is highly recommended to account for the presence of any calcium source during the design of the chemical formulation for barium sulfate scale removal using DTPA. Therefore, DTPA treatment formulation is recommended in sandstone formations. Field results can be completely different from laboratory results if Ca2+ chelation from carbonate rocks is ignored.
Hassan, Amjed (King Fahd University of Petroleum & Minerals) | Mahmoud, Mohamed (King Fahd University of Petroleum & Minerals) | Al-Majed, Abdulaziz (King Fahd University of Petroleum & Minerals) | Al-Nakhli, Ayman (Saudi Aramco) | BaTaweel, Mohammed (Saudi Aramco) | Elktatany, Salaheldin (King Fahd University of Petroleum & Minerals)
Condensate banking is a common problem in tight gas reservoirs because it diminishes the gas relative permeability and reduces the gas production rate significantly. CO2 injection is a common and very effective solution for condensate removal in tight gas reservoirs. The problem with CO2 injection is that it is a temporary solution and has to be repeated frequently in the field in addition to the supply limitations of CO2 in some areas. Also, the infrastructure required at the surface to handle CO2 injection makes it expensive to apply CO2 injection for condensate removal.
In this paper, a new permanent technique is introduced to remove the condensate by using a thermochemical technique. Two chemicals will be used to generate in-situ CO2, nitrogen, steam, heat, and pressure. The reaction of the two chemicals downhole can be triggered either by the reservoir temperature, or a chemical activator. Two chemicals will start reacting and produce all the mentioned reaction products after 24 hrs. of mixing and injection. Also, the reaction can be triggered by a chemical activator and this will shorten the time of reaction. Coreflooding experiments were carried out using actual condensate samples from one of the gas fields. Tight sandstone cores of 0.9 mD permeability were used.
The results of this study showed that, the thermochemical reaction products removed the condensate and reduced its viscosity due to the high temperature and the generated gases. The novelty in this paper is the creation of micro-fractures in the tight rock sample due to the in-situ generation of heat and pressure from the thermochemical reaction. These micro-fractures reduced the capillary forces that hold the condensate and enhanced its relative permeability. The creation of micro-fractures and in turn the reduction of the capillary forces can be considered as permanent condensate removal.
Murtaza, Mobeen (King Fahd University of Petroleum & Minerals) | Mahmoud, Mohamed (King Fahd University of Petroleum & Minerals) | Elkatatny, Salaheldin (King Fahd University of Petroleum & Minerals) | Majed, Abdulaziz Al (King Fahd University of Petroleum & Minerals) | Chen, Weiqing (King Fahd University of Petroleum & Minerals) | Jamaluddin, Abul (King Fahd University of Petroleum & Minerals)
In cementing operations of deep oil and gas wells, long term integrity of the well is highly dependent on the cement sheath. Obtaining success rate in cementing operations has been subjected to a myriad of challenges, as drilling into deeper, high pressure/high temperature horizons is done. To gain long term integrity of cement sheath, a successful placement of cement slurry plays a pivotal role. So, the design of suitable rheological properties helps characterize the cement pumpability, mixability, and displacement rates for adequate removal of mud. So, the design of cement slurry for HPHT and deviated wells has become a complex task. Recently employing nano-materials in improved oil recovery, designing of drilling fluids as well as hydrocarbon well cementing has been the focus of many studies. The intrinsic characteristics of being smaller in size, while at the same time providing a larger surface area, nanomaterials can prove to be a game-changer for the challenges faced in HPHT cementing. This paper reproduces the outcomes of an investigational study conducted to determine the effect of nanoclay as an additive on rheological properties of Type-G cement slurry under various temperature conditions. Nano-clay with Class G cement in two different concentrations 1% and 2% by weight of cement, mixed and tested under different temperature conditions (37°C, 50°C, 60°C & 80 °C). Additionally, nano-clay based cement mixtures were prepared by substituting cement with 1%, 2% and 3% of nano-clay by weight of cement(BWOC), and admixed with silica flour, along with various chemical admixtures. American Petroleum Institute (API) standard-10B was followed to condition the slurry at predetermined temperature, while the slurry was under atmospheric pressure. This conditioning was followed by the measurement of rheological properties. Results of this investigation demonstrate that incorporation of nano-clay advances the rheology of prepared cement slurry that could aid in mud-displacement and anti-settling as per the requirements.
Ahmed S, Abdulmalek (King Fahd University of Petroleum & Minerals) | Elkatatny, Salaheldin (King Fahd University of Petroleum & Minerals) | Ali, Abdulwahab Z (King Fahd University of Petroleum & Minerals) | Mahmoud, Mohamed (King Fahd University of Petroleum & Minerals) | Abdulraheem, Abdulazeez (King Fahd University of Petroleum & Minerals)
Rate of Penetration (ROP) means how fast the drilling bit is drilling through the formations. It is known that in the oil and gas industry, most of the well cost is taken by the drilling operations. So, it is very crucial to drill carefully and improve the drilling processes. Nevertheless, it is hard to know the influence of every single parameter because most of the drilling parameters depend on each other, and altering an individual parameter will have an impact on the other. Due to the difficulty of the drilling operations, up to the present time, there is no dependable model that can estimate the ROP correctly. Consequently, using the artificial intelligence (AI) in the drilling is becoming more and more applicable because it can consider all the unknown parameters in building the model. In this work, a real filed data that contain the real time surface drilling parameters and the drilling fluid properties were utilized by fuzzy logic (FL) to estimate the rate of penetration. The achieved results proved that fuzzy logic technique can be applied effectively to estimate the rate of penetration accurately with R 0.97 and AAPE 7.3%, which outperformed the other ROP models. The developed AI models also have the advantage of using less input parameters than the previous ROP models.
Ahmed S., Abdulmalek (King Fahd University of Petroleum & Minerals) | Mahmoud, Ahmed Abdulhamid (King Fahd University of Petroleum & Minerals) | Elkatatny, Salaheldin (King Fahd University of Petroleum & Minerals) | Mahmoud, Mohamed (King Fahd University of Petroleum & Minerals) | Abdulraheem, Abdulazeez (King Fahd University of Petroleum & Minerals)
Pore and fracture pressures are a critical formation condition that affects efficiency and economy of drilling operations. The knowledge of the pore and fracture pressures is significant to control the well. It will assist in avoiding problems associated with drilling operation and decreasing the cost of drilling operation. It is essential to predict pore and fracture pressures accurately prior to drilling process to prevent various issues for example fluid loss, kicks, fracture the formation, differential pipe sticking, heaving shale and blowouts. Many models are used to estimate the pore and fracture pressures either from log information, drilling parameters or formation strengths. However, these models have some limitations such as some of the models can only be used in clean shales, applicable only for the pressure generated by under-compaction mechanism and some of them are not applicable in unloading formations. Few papers used artificial intelligence (AI) to estimate the pore and fracture pressures. In this work, a real filed data that contain the log data and real time surface drilling parameters were utilized by support vector machine (SVM) to predict the pore and fracture pressures.
The demand for unconventional gas is rapidly increasing to provide enough energy to maintain sustainable growth for industrial countries. Even oil producers can develop UG to be directed to internal industrial and power consumptions. As Unconventional gas reservoirs are located in deep high-stress formations, one of the critical challenges gas producers are facing is to develop a cost effective stimulation method that can reduce production cost to lower than Break-even.
In this paper a novel stimulation method, based on thermochemicals, is introduced. Thermochemicals when injected in tight reservoirs generate localized pressure-pulses, which result in creating microfractures, improve permeability and increase stimulated reservoir volume (SRV). Tight core samples were treated with thermochemicals and the impact on mechanical properties were studied. Generated localized pressure was clearly detected during Coreflood treatment. Microstructural and mineralogical properties were also investigated using microscopy and spectroscopy. CT-scan, micro CT-Scan, Young's modulus, Poisson's ratio and ultrasonic velocities were measured pre and post treatment. Results showed creation of fractures and microfractures, which resulted in improved rock conductivity.
Results show that, micro-factures are created inside the used sample due to the in-situ generation of heat and pressure. The density of those micro-factures is strong function of the chemical concentration and the injected volume. Creation of micro-factures leads to improve the formation conductivity and reduce the capillary forces, therefore, enhances the hydrocarbon recovery. The outcome of this study is to understand the impact of thermochemical treatment on rock integrity. The ultimate objective is to establish a relationship between the injected chemicals and the alterations of formation properties such as permeability and porosity. This work will serve as a baseline for designing and conducting thermochemical operations for hydrocarbon reservoirs.
In this study a novel stimulation technique to increase stimulated reservoir volume (SRV) is presented. In basins with excessive tectonic stresses, the current novel treatment can become an enabler to deeply stimulate well stages which otherwise left untreated. A new methodology is developed to lower fracturing cost and increase unconventional gas production. A better connectivity reduces the required number of hydraulic fracturing-stages.
Probe permeameter (also known as Mini-permeameter) has been widely used in many field and laboratory applications where in-situ measurements and spatial distributions of permeability are needed. Mini-permeameter measurements have become popular techniques for collecting localized permeability measurements in both laboratory and field applications. It is designed to obtain fast, cheap, intensive and non-destructive permeability measurements and to describe the spatial arrangement of permeability.
In this work, the effect of vertical and horizontal anisotropy on the probe permeameter measurements was investigated. A numerical simulation model for the rectangular system representing a porous rock sample was built based on finite difference discretization of steady-state flow of an incompressible single-phase fluid in a three-dimensional (3D) system. The seal and tip of the probe permeameter are represented by no-flow boundary and constant pressure boundary, respectively. All the sides of the sample are represented by a constant-pressure boundary in which the sample is exposed to the atmosphere. The investigation was conducted by examining different permeability anisotropy ratios. These include fully isotropic sample, different vertical anisotropy ratios in a horizontally-isotropic sample, different vertical anisotropy ratios at different horizontal anisotropy ratios. All these investigations are performed at a constant probe injection pressure of 50 psig at the injection tip.
The results obtained showed the clear effect of anisotropy on the probe permeameter measurements and were expressed in dimensionless parameters. These dimensionless parameters include the ratio between the flow rate measurements at different directions for different vertical and horizontal anisotropy ratios. They also include the dimensionless pressure drop for the pressure drop measurements at different directions. From the plots of these dimensionless parameters, the permeability at different directions can be evaluated from a few steady-state flow rate and pressure drop measurements at different directions on a rectangular core sample. Therefore, a practical procedure for evaluating permeability anisotropy from probe permeameter measurements is also described.
Reservoir evaluation of source rock is still a challenge because the geochemical assessment of the kerogen content is complicated and time consuming. Existing traditional methods to characterize kerogen involves the removal of inorganic minerals which is a critical preliminary step. The incomplete isolation of kerogen may introduce some errors and uncertainties in kerogen content estimation. The alteration of kerogen microstructure during this process has also been documented. The current approach still requires input from geochemical measurement of total organic carbon (TOC) while the conversion of TOC to kerogen volume requires the precise value of a conversion factor and kerogen density. Overall, there is yet a standard lab or field scale approach to characterize kerogen content. These difficulties and uncertainties prompt the motivation to attempt a new methodology to quantify the kerogen content of unconventional shale from porosity measurements.
Porosity is the basic rock property that is related to the volumetric average of pore space. The distinction between the total and effective porosity is meaningless for shale and this characteristic property has enabled the preservation of its organic content. The recent popularity and growth of different measurement techniques is in part closely tied to the near zero porosity of shale. Two special cases of practical interest are NMR and density porosity measurements which can both be measured in the rock physics lab and well logs. NMR porosity is sensitive to 1H which is naturally enriched in kerogen whereas density porosity must be calibrated to the mineral matrix.
Based on porosity measurements, the emerging aproach is that the kerogen volume fraction is the contrast between NMR and density porosity. Although, the theoretical basis of this approach is not satisfactory, it is straightforward and far less complicated than the existing approaches to quantify kerogen content. We investigate this concept further based on laboratory measurement. We conducted laboratory measurements of NMR porosity, bulk density, grain density and TOC on Qusaiba shale to characterize its kerogen content. In our approach, we conducted the NMR experiment on the shale samples in the dry state without fluid saturation.
Ahmed S, Abdulmalek (King Fahd University of Petroleum & Minerals) | Elkatatny, Salaheldin (King Fahd University of Petroleum & Minerals) | Ali, Abdulwahab Z (King Fahd University of Petroleum & Minerals) | Abdulraheem, Abdulazeez (King Fahd University of Petroleum & Minerals) | Mahmoud, Mohamed (King Fahd University of Petroleum & Minerals)
Fracture pressure is a critical formation condition that affects efficiency and economy of drilling operations. The knowledge of the fracture pressure is significant to control the well. It will assist in avoiding problems associated with drilling operation and decreasing the cost of drilling operation. It is essential to predict fracture pressure accurately prior to drilling process to prevent various issues for example fluid loss, kicks, fracture the formation, differential pipe sticking, heaving shale and blowouts.
Many models are used to estimate the fracture pressure either from log information or formation strengths. However, these models have some limitations such as some of the models can only be used in clean shales, applicable only for the pressure generated by under-compaction mechanism and some of them are not applicable in unloading formations. Few papers used artificial intelligence (AI) to estimate the fracture pressure. In this work, a real filed data that contain only the real time surface drilling parameters were utilized by artificial neural network (ANN) to predict the fracture pressure.
The results indicated that artificial neural network (ANN) predicted the fracture pressures with an excellent precision where the coefficient of determination (R2) is greater than 0.99. In addition, the artificial neural network (ANN) was compared with other fracture pressure models such as Matthews and Kelly model, which is one of the most used models in the prediction of the fracture pressure in the field. Artificial neural network (ANN) model outperformed the fracture models by a high margin and by its simple prediction of fracture pressure where it can predict the fracture pressure from only the real time surface drilling parameters, which are easily available.