Phi, Thai (University of Oklahoma) | Elgaddafi, Rida (University of Oklahoma) | Al Ramadan, Mustafa (University of Oklahoma) | Ahmed, Ramadan (King Fahd University of Petroleum & Minerals) | Teodoriu, Catalin (University of Oklahoma)
Most untapped promising energy resources in the world are associated with extreme downhole environment conditions. Applying the conventional method of well construction and operation for extreme downhole conditions poses severe challenges for the safety and longevity of the well. Governments and independent standardization organizations have developed several regulations regarding maintaining well integrity. Nevertheless, methods of completing and operating Extreme High-Pressure-High-Temperature (XHPHT) wells as well as geothermal wells have not yet been standardized. Preserving well integrity throughout the life cycle of a well is very crucial. Failure in well integrity can lead to huge operational and environmental risk and increase the energy cost.
This paper critically reviews the causes and solutions of well integrity issues in XHPHT and geothermal wells. After giving an overview of these wells, the paper discusses the well barriers at different ages. It also presents the conditions that lead to well integrity issues. Furthermore, the article discusses comprehensively the influence of acidic environment on cement and casing degradation at HPHT and summarizes the most recent research findings and development strategies in mitigating the integrity issues.
Previous studies revealed that the integrity of well barriers is highly affected by the degradation of drilling and completion fluids, cement, and tubular materials. The main causes of the well integrity loss are the lack of understanding of downhole conditions, inappropriate well construction practices, poor selection of the casing material and cementing type as well as inadequate design verification and validation on the downhole specimen. The well barriers are inter-related to each other as the destruction of one barrier may lead to the dismantling of the entire well barrier envelope. The XHPHT and geothermal wells share numerous similar barrier integrity issues, but they also have some unique problems due to the nature of their own operations. Although there is a significant advancement in solving the well integrity issues for the extreme downhole conditions, a sizable technology gap still exists in constructing and operating XHPHT and geothermal wells.
The current market conditions and the advancement in technologies are making the development of XHPHT wells more economically feasible. This paper serves as a review of the current research and development regarding well integrity issues for XHPHT and geothermal wells.
Al-Enezi, Badriya (Kuwait Oil Company) | Liu, Peiwu (Schlumberger) | Liu, Hai (Schlumberger) | Kanneganti, Kousic Theja (Schlumberger) | Aloun, Samir (Kuwait Oil Company) | Al-Harbi, Sultan (Kuwait Oil Company) | Al-Ibrahim, Abdullah (Kuwait Oil Company)
A recent study showed that Tuba reservoir, a limestone-rich formation, has the highest oil in-place of all upcoming reservoirs in North Kuwait. This tight formation has three main layers - Tuba Upper (TU), Tuba Middle (TM), and Tuba Lower (TL) with several reservoir units alternating with non-pay intervals. The reservoir units contain significant proven oil reserves; however, production performance after conventional acid fracturing treatments has been historically subpar. As part of new development plan, two horizontal wells, one in TU and one in TL were drilled to evaluate the production potential of a new completion strategy and technologies.
This paper presents one such technology, a single-phase retarded acid system used as a pilot project study. In contrast with previous conventional emulsified acid systems, the single-phase retarded acid minimized tubing friction, thus enabling high pumping rates for the entire treatment. Alternating with the acid system, a viscoelastic surfactant-based leakoff control fluid system allowed the acid stages to reach deeper into the formation. To aid, degradable fiber technology was pumped in several stages to achieve near-wellbore diversion and further control leakoff into large natural fractures, thus improving the stimulated reservoir volume. These fibers are designed to completely degrade with time and temperature after the treatment. Delivery of the complex acid fracturing treatment was optimized in real time for each stage based on bottomhole pressure trend and response.
Combining a new single-phase retarded acid system with chemical diversion technology has proved to be effective in maximizing lateral coverage and etched fracture half-length. Post-treatment evaluation of TU horizontal well revealed the initial production was as much as 150% higher than offset vertical wells after conventional treatments with gelled acid and as high as 100% higher than a previous multistage horizontal well treated with emulsified acid. The TL horizontal well was just put into production recently and is showing encouraging results considering the lower reservoir quality compared to TU formation.
The success of this technique and technical combination delivered breakthrough results for this region and has engaged new interest in developing the Tuba reservoir.
Khan, Riaz (ADNOC) | Al Hanaee, Ahmed (ADNOC) | Al Tameemi, Kate (ADNOC) | Kurniawan, Redy (ADNOC) | Omonigho, Neil (ADNOC) | Gueddoud, Abdelghani (ADNOC) | Abdelaal, Atef (ADNOC) | Vantala, Aurifullah (ADNOC)
The Gachsaran Formation across Onshore Abu Dhabi and possibly across U.A.E poses high potential of generating Shallow Biogenic Gas (mainly methane) and as such has taken the attention to further investigate, understand and evaluate its capability for promising Gas Resources. The paper provides a detailed G&G analysis that has potentially allowed an appropriate characterization of this unique formation that has first time uncovered interesting data responses in differentiating the sweet spot.
For the first time in the history of U.A.E., new data was acquired targeting specifically the Miocene, Gachsaran Formation. This includes; 2D Seismic and party 3D Seismic interpretations, thousands of feet continuous core, conventional and advanced subsurface and surface loggings, Formation Pressure, Fluid sampling, Geochemical and Geomechanical labs measurements, stimulations and Frac tests data. The Gachsaran Formation is very challenging due to complex, thinly bedded and intercalated lithological varitions, and tightness provides difficulties in identifying the promising areas of Gas bearing layers. A comprehensive analysis was performed, in the light of regional understanding, by integrating the results of all available data in the form of correlation, cluster analysis, cross plotting and well based rock physics to differentiate the effect of Gas existence within the formation. The potential zones were further tested and results were integrated to confirm the analysis.
The Gachsaran Formation has been subdivided into Lower, Middle and Upper Gachsaran Members. The Lower Member is predominantly evaporitic, becoming more argillaceous carbonate and shale –bearing in the the Middle Member with comparatively less anhydrites. The Upper Member contains mainly anhydrites with interbedded shales and carbonates. The potential sequences which represent high Total Organic Carbon and Gas Shows are found within the Middle Gachsaran.
Consequently, the Middle Gachsaran Member was analyzed based on the robust data acquisition performed. Several relationships among GR, TOC, Gas shows, Lithology, RHOB, NPHI, Sonic, AI, Vp/Vs, Gradient Impedance and XRD Clay mineralogy have been attempted to check possible identification of Gas existence effect on the data. This has led to identify the sweet spots caused by the existence of any dominant Gas within the Study Area. The potential zones were confirmed by well testing. Furthermore, data variables were distributed within a 3D Grid and based on the analysis performed the area of sweet spots were identified. In the next phase of the study, the results will be integrated with the upcoming Geophysical Seismic Inversion studies to further optimize the possibility of identifying the sweet spot across the Study Area.
The robust data acquisition targeting Gachsaran was performed first time in the history of U.A.E. The results are encouraging in establishing the relationship to identify the dominant existence of Gas effects within the area. The estimation of realistic Gas In-Place and its confirmation of commercial discovery will open a new era of Shallow Gas resources within U.A.E.
Machine learning has attracted the attention of geoscientists over the years. In particular, image analysis via machine learning has promise for application to exploration and production technologies. Demands have grown for the automation of carbonate lithology identification to shorten the delivery time of work and to enable unspecialized engineers to conduct it. The image analysis of carbonate thin sections is time consuming and requires expert knowledge of carbonate sedimentology. In this study, the authors propose an image analysis technique based on deep neural network for carbonate lithology identification of a thin section, which is an important image analysis process required for oil and gas exploration. In addition, the authors consider that porosity and permeability variations in the same facies are controlled by the grain, cement, pore, and limemud contents. If the contents are accurately measured, the porosity and permeability can be determined more accurately than by using traditional methods such as point counting. The elucidation of the complex relation of porosity and permeability is the objective of automation of carbonate lithology identification. To perform image analysis of the thin section, the authors prepared a data set mainly comprising pictures of the Pleistocene Ryukyu Group, which were composed of reef complex deposits distributed in southern Japan. The data set contains 306 thin section pictures and annotation data labeled by a carbonate sedimentologist. The rock components was divided into four types (grain, cement, pore, and limemud). A convolution neural network (CNN) was utilized to train the model. After training the neural network, each of the four categories was interpreted by the trained model automatically. Resultantly, the accuracy of automatic Dunham classification was 90.6% and the mean average test accuracy of category identification was 83.9%. The interpretation seems highly consistent between human vision and machine vision in both the overview and pixelwise scales. This result indicates that it has sufficient potential to assist geologists and become a basic tool for practical applications. However, the accuracy of category identification is still insufficient. The authors believe that the model requires higher quality supervised data and a greater number of supervised data.
AL-Rashidi, Hamad (Kuwait Oil Compaby) | Jamsheer, Abdullah (Kuwait Oil Compaby) | AL-Azmi, Talal (Kuwait Oil Compaby) | Muhsain, Batoul (Kuwait Oil Compaby) | Abu-Eida, Abdullah (Kuwait Oil Compaby) | AL-Methen, Badriya (Kuwait Oil Compaby) | Mousa, Saad (Kuwait Oil Compaby) | AL-Harbi, Faseil (Kuwait Oil Compaby) | Duncan, Bruce (Kuwait Oil Compaby) | Safar, Abdulaziz (Kuwait Oil Compaby) | AL-Azmi, Waled (Kuwait Oil Compaby) | Desoky, Waleed (Kuwait Oil Compaby) | AL-Sabah, Fahad (AL-Thurya) | AL-Yaseen, Musaeb (Burgan One) | AL-Hajri, Mohsen (BG) | AL-Mutwa, Bandar (AAA) | AL-Awadhi, Hisham (AAA) | Almeida, Dwane (BG) | AL-Zanki, Farooq (Burgan One)
The strategy of the Kuwait Oil Company (KOC) is to implement key/emerging technologies at a country wide scale to meet future oil demand and production targets as planned in KPC 2040 strategy through overcome the field's challenges. KOC's Optimization strategy focuses on:
Increased and optimize oil production from production optimizations Extension of field life
Increased and optimize oil production from production optimizations
Extension of field life
Production interruption associated with pressure build up in reservoir, wellbore and flow lines have observed among many wells in West Kuwait fields perforated in Upper Burgan formation, which has a great impact on the company strategy. Tight emulsion phenomena is consider one the most challenging problems in West Kuwait wells due to the nature of asphaltenic crudes and high water cut production percentage. Traditional approaches to reduce high pressure and break the emulsion phase through injecting chemical near wellhead or in annuls is usually not successful in most cases and require large amount of chemical. Due to the complexity of this issue, a novel approach was used in this study to identify the main causes of oil production reduction and overcome the challenge to maximize oil production in West Kuwait fields.
Increased demand for gas in the recent years has motivated Exploration companies to revisit erstwhile overlooked Miocene Biogenic gas potentials, onshore Abu Dhabi. This paper detail how advanced geophysics techniques including rock physics forward modeling and inversion has been integrated to understand the distribution of potential gas bearing zones in this complex unconventional setting where inter-well information is limited. The results integrated with understandings from other disciplines support drilling and field appraisal strategy in the area.
The Miocene Formation of interest consists of an Upper, Middle and Lower unit, with varying levels of complexities and hydrocarbon presence identified from drilled wells. We show how we integrated all available data including logs, core, fluids, cuttings, mud-gas, petrophysical and seismic information to constrain the seismic forward model and invert the seismic data to define potential for gas presence in the area. Lithologic boundaries were defined from cuttings and geologic correlations. Half-space rock properties analyses and well ties provided understanding of the seismic responses, and the geologic picks mapped accordingly. Gassmann fluid substitution were carried out using conditioned Vp, Vs and density logs to understand the sensitivity of the lithologies to different pore fluid fill including brine and different gas proportions. AVO forward modeling was also carried out to understand if gas ‘sweet spots’ may be visible from analyses of amplitudes. Rock physics plots were analysed including AI, SI, GI, PI and Lame's parameters to establish relationship to reservoir properties, and optimum discriminators of fluid, porosity and TOC were accordingly determined. The low frequency model was developed from logs, and prestack 2D seismic data up to 40° were inverted for elastic impedances. Bayesian rock type classification scheme was deployed to extract potential gas prolific areas.
Seismic rock properties analyses provided invaluable insight to the reservoir characterisation strategy for the Biogenic gas formation. The analyses showed that delineating gas presence is challenging using conventional amplitude or AVO analyses techniques. Potential for fluid optimization exists from analyses of poisson's impedance (PI) as well as extended elastic impedance at the fluid projection with reasonable certainty. Pre-stack simultaneous inversion of the seismic lines was carried out, followed by Bayesian rock type classification to identify regions of increased gas potential in areas of seismic coverage
This paper represents for the first time integrated seismic rock properties and inversion techniques are applied to delineate an unconventional Biogenic gas reservoir. The results hold potential benefit for well placement and input to distribution of reservoir properties in the geologic model. The method will be extended to analyzing the gas potential from the currently acquired mega 3D seismic over Abu Dhabi.
Taher, Ahmed (Abu Dhabi National Oil Company) | Al Hanaee, Ahmed (Abu Dhabi National Oil Company) | Frsnco, Bernardo (Abu Dhabi National Oil Company) | Chitrao, Amogh (Abu Dhabi National Oil Company) | Abdelaal, Atef (Abu Dhabi National Oil Company) | Popa, Desdemona (Abu Dhabi National Oil Company)
Recently there has been a growing interest in gas exploration, much of this focus has been directed toward thermogenic gas derived from cracking kerogen in the highly mature kitchens. However, a significant proportion of the global gas reserve is not thermogenic but of bacterial origin (
The recent exploration wells drilled in the northeast onshore Abu Dhabi showed elevated total gas readings during the drilling of the Gachsaran formation. Consequently, mud-weight was increased to control the gas flow. In addition, the recorded wireline logs indicate the presence of relatively high hydrocarbon saturations in several high porous zones of Gachsaran and Asmari formations.
To assess the productivity and commerciality of the Biogenic gas potential in Abu Dhabi, several exploration wells are planned to be drilled before the end of 2019. The positive results of these wells will open the door for a new era of sweet gas exploration activities in Abu Dhabi and its surrounding areas. The primary gas reservoirs are thin carbonate and clastics layers in the Gachsaran Formation at a depth that ranges between 1600-5200 feet below sea level.
Organic carbon isotopes, Rock Eval analysis, TOC log data and gas shows analysis indicated that the methane gas found in the Gachsaran Formation is of a biogenic origin and sourced mainly from the organic-rich argillaceous limestone of the Middle Gachsaran.
Gachsaran formation is comprised of alternating thin layers of anhydrite, limestone, marl and shale sediments in addition to the presence of salt layers in the lower part. This mixed lithology resulted in the reservoirs property deterioration in particular by shale and anhydrite nodules cementation.
The biogenic basin areal extent, significant thickness of the Gachsaran in this basin and the organic richness distribution, conclude possible generation of a huge volume of biogenic gas in northeast onshore Abu Dhabi. However, additional work is required to estimate the volume of gas that is accumulated and that can be produced from the Gachsaran and Asmari formations.
Halokinesis has strongly stimuluses the Abu Dhabi petroleum system. During the Late Precambrian, the basement terranes of the Arabian and adjoining plates were fused along the northeastern margin of the African Gondwanaland plate. This phase was followed by continental rifting and intra-continental extension. The Arabian Infracambrian extensional system established rifted salt basins in the Zagros region, South Oman and in the Arabian Gulf. The Hormuz salt in these areas contains basalt and rhyolite, suggesting tectonic extension at this time. The Zagros thrust fault and Dibba transform fault define the current limits of the Hormuz Complex of the Arabian Gulf. As a passive margin during Paleozoic time, the Arabian plate accumulated a continentally influenced shallow marine sequence characterized by interbedded siltstones, sandstones, shales and carbonates sediments. The Late Ordovician-Early Silurian glaciation interrupted the Paleozoic deposition by lowering sea level in the Late Silurian and Late Carboniferous-Early Permian glaciation.
Salt movement was started an extensional phase in Permo-Jurassic with the Neo-Tethys opening and basement faults reactivation. Followed by Cretaceous compression stress due to Afro-Arabian Plate movement. The third phase happened by Late Cretaceous with the closing of the Neo-Tethys. The salt was finally pierced to the surface by Mid Tertiary compression stress forces accompanied with Oman thrusting and Zagros folding. Since Miocene uplift, the salt movement extended until present day onwards. Previously, the pierced salt was considered stacked, but subsidence measurements indicating salt is still moving in some islands reaching about 2cm per year.
This paper uses 3D seismic, core data and outcrops investigations to assess the geometry, kinematics, and the halokinetic phases that stimuluses the hydrocarbon exploration targets. The paper revisited the flowage phases of the salt in Abu Dhabi, investigated the accompanying fault geometries and relate this to the structural styles. The diapiric anticlines forming during salt movement phases forming domal structures with radial faults. Contradicting what is known, the Miocene-recent strata are tilted indicating the continuation of the salt movement. The Hormuz salt is characterized by a regionally consistent stratigraphy, formed of evaporites interbedded with clastic and carbonate sediments with dolomite intervals and vein intrusions of volcanic rocks.
Interpreted faults were categorized into three families, Type I comprising domal radial faults, Type II representing faults triggered salt movements and Type III describing salt movements triggered faults. The first type is characterizing itself by its location relative to the crystal parts of the domes. The relatively low overburden pressure at the crest of the diapir and the original high dip angles of these fault planes favor salt intrusions near the diapir crest. Depending on the salt movement phases, the generated cycles of these faults, are characterized by different dips and areas of extension, while the other two categories can be differentiated as well. At the time of salt movement initiation, these faults were incipiently intruded by salt for relieving the intense internal overpressure in the salt body. These pressures are due to the compression forces associated with the salt movement, the buoyancy effects compensating the density difference between salt and overlying sediments and the tectonic compression forces. The latter is the reasonable mechanisms that allow salt penetration along fault planes and bedding planes.
This paper provides evidences that salt movements impact the petroleum system, especially traps, as if the salt movement preceding the hydrocarbon migration, this leads to faults sealing and the reverse is also applied.
Low rates of penetration (ROP) were experienced in an area with well-known lithology. The vast drilling experience and similarity of drilling conditions in the area, provided the operator with enough data to improve the well schedule and cost performance through the use of machine learning.
Machine learning, specifically artificial neural networks (ANN), is a statistical tool to find relations between multiple inputs. Details that would have been missed or considered outliers by a mathematical model can be accounted for and explained in the ANN model. The ANN was trained on thousands of real time data points recorded from selected wells in a specific depth interval. Typical drilling parameters such as weight on bit, rotary speed, bit hydraulics, lithological properties, and dogleg severity were the input parameters chosen in the model to generate ROP. Once the model was calibrated to historical data, it was used to find the best parameters to maximize ROP.
R squared factors were 0.729 and 0.675 for 12.25 in. and 17.5 in. sections repectively. This was achieved with an ANN structure of 2 hidden layers consisting of 5 nodes each. Sensitivity analysis identified bit hydraulics, weight on bit, and rotary speed as the major parameters impacting ROP. The ROP model was used to conduct a "virtual drill-off test" to identify drilling parameters that maximize ROP. ROP dependency on weight on bit and lithological analysis suggests bit design can be further improved. Bit hydraulics showed that higher flow rate was needed in sections with higher overbalance. Optimum drilling parameters were tested on four wells and resulted in more than 50% higher ROP compared to original field data.
In an industry increasingly dominated by big data, separating the clean data from the "noise" will be a vital topic. This paper aims to provide a blueprint for the use machine learning to optimize ROP in a manner that is simple and easily replicated.
Abbas, Ahmed K. (Iraqi Drilling Company) | Assi, Amel H. (Baghdad University) | Abbas, Hayder (Missan Oil Company) | Almubarak, Haidar (King Saud University) | Al Saba, Mortadha (Australian College of Kuwait)
The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the modeling part, a one-dimension mechanical earth model (1D MEM) parameters, drilling fluid properties, and rig- and bit-related parameters, were included as inputs. The optimizing process was then performed to propose the optimum drilling parameters to select the drilling bit that provides the maximum possible ROP. To achieve this, the corresponding mathematical function of the ANNs model was implemented in a procedure using the genetic algorithm (GA) to obtain operating parameters that lead to maximum ROP. The output will propose an optimal bit selection that provides the maximum ROP along with the best drilling parameters. The statistical analysis of the predicted bit types and optimum drilling parameters comparing the actual flied measured values showed a low root mean square error (RMSE), low average absolute percentage error (AAPE), and high correction coefficient (R2). The proposed methodology provides drilling engineers with more choices to determine the best-case scenario for planning and/or drilling future wells. Meanwhile, the newly developed model can be used in optimizing the drilling parameters, maximizing ROP, estimating the drilling time, and eventually reducing the total field development expenses.