Even though coring of rocks is the best way to characterize reservoir and source rocks geologically and petrophysically, this method is considered expensive, having a relatively high cost per foot. Alternatively, side-wall cores and cuttings are widely used in reservoir characterization at a relatively low cost. However, this method has limitations related to cuttings bad physical conditions, size, mixed lithological and mineralogical characteristics which make the commonly used conventional evaluation methods not applicable. This study introduces a robust combination of digital and conventional core analysis methods to overcome these limitations and characterize reservoir and shale cuttings derived from two hydrocarbon-bearing formations in New Zealand.
Initially, all cuttings from both formations were screened based on their cutting sizes and later based on the visually observed textures using the stereomicroscope. This helped in selecting representative cuttings for the main identified textures. These cuttings were CT imaged at a resolution ranging from 40 to 4 microns/voxel resolution in order to confirm their rock textures and sedimentary structures for better characterization results. Next, mercury injection capillary pressure (MICP), X-ray diffraction (XRD), and petrographical analysis were conducted on all selected cuttings with different rock textures in order to understand the pore types, textural variations, diagenetic overprints and mineralogy of the cuttings samples. Then, they were scanned at optimum resolutions using Micro CT and 3D FIB-SEM microscopies. Finally, all acquired images were segmented digitally and 3D rock volumes were created. These volumes were used in computing porosity, permeability, formation factor resistivity (FRF) and poroperm trends digitally using numerical simulation techniques.
Conventional and digital rock analysis showed that the cuttings derived from the reservoir interval are composed of an argillaceous sandstone with a very good computed porosity (18% up to 31%) and permeability (30 to 200 mD). On the other hand, the cuttings derived from the shale source rock interval, which were predominately composed of clay minerals, have a computed porosity of 12% to 13% (mainly inorganic pores) and an absolute permeability in the range of 0.5 to 4 Micro-Darcy. The digital poroperm trend analysis identified distinct poroperm trends for each formation which helped in understanding their petrophysical aspects.
This integration between conventional and digital methods provided better geological and petrophysical understanding of both formations using a limited number of cuttings, less cost and time.
Africa (Sub-Sahara) Oil was discovered at the Ekales-1 wildcat well located in Block 13T in northern Kenya. The well has a potential net pay of between 197 and 322 ft in the Auwerwer and Upper Lokone sandstone formations. Tullow (50%) operates 13T with partner Africa Oil (50%). The Mzia-3 appraisal well in Block 1 off Tanzania encountered a combined total of 183 ft of net pay in the Lower and Middle sands and confirmed reservoir quality in line with that seen in the Mzia-1 and Mzia-2 wells. Asia Pacific The Luba-1 offshore well on Brunei Block L was spudded. The well will evaluate the hydrocarbon potential of the Triple Junction structure. Serinus has a 90% interest in Block L, through indirect wholly owned subsidiaries Kulczyk Oil Brunei (40%) and AED SEA (operator, 50%).
Africa (Sub-Sahara) Gas was discovered at two separate levels in the Mronge-1 well in Block 2 offshore Tanzania. The discovery is estimated at between 2 and 3 Tcf of natural gas in place, bringing Block 2's estimated total in-place volumes up to 17 to 20 Tcf. Statoil (65%) operates the Block 2 license on behalf of Tanzania Petroleum Development Corporation, and partners with ExxonMobil Exploration and Production Tanzania (35%). Oil was discovered at the Agete-1 exploration well on Block 13T in northern Kenya. The well, drilled to a total depth of 1929 m, encountered 330 ft of net oil pay in good-quality sandstone reservoirs. Tullow Oil (50%) is the operator with partner Africa Oil (50%). Asia Pacific Indonesia announced plans to offer 27 oil and gas blocks in 2014 in regular tenders and direct offers.
Africa (Sub-Sahara) Drilling began on the Bamboo-1 well, located around 35 miles offshore Cameroon in the Ntem concession. The Bamboo prospect is a basin floor fan target within an Upper Cretaceous play. The well will be drilled to an estimated depth of 4200 m. Murphy Cameroon (50%) is the operator, with partner Sterling (50%). The Nene Marine 3 exploration well--located in the Marine XII block, which is around 17 km offshore Congo--encountered a wet gas and light oil accumulation in a presalt clastic sequence Eni (65%) operates the Marine XII block, with partners New Age (25%) and Société Nationale des Pétroles du Congo (10%). CNPC said PetroChina is now building a production facility capable of pumping 4 Bcm/yr.
Africa (Sub-Sahara) BG Group discovered gas in the Taachui-1 well and sidetrack in Block 1, offshore Tanzania. The drillship Deepsea Metro Idrilled Taachui-1 close to the western boundary of Block 1, then sidetracked the well and drilled to a total depth of 4215 m. The well encountered gas in a single gross column of 289 m within the targeted Cretaceous reservoir interval. Net pay totaled 155 m. Estimates of the mean recoverable gas resources are around 1 Tcf. Statoil (65%) and co-venturer ExxonMobil (35%) made a sixth discovery--the Piri-1 well--in Block 2 offshore Tanzania. Piri-1 was drilled by drillship Discoverer Americas, at a water depth of 2360 m.
Africa (Sub-Sahara) Eni finished a production test on its Minsala Marine 1 NFW well, located in Marine XII block, 35 km offshore The Republic of the Congo. During the test, the well delivered natural flow in excess of 5,000 B/D of 41 API crude and 14 MMcf/D of natural gas from a 37-m opened section of the discovery's 420-m column. Eni (65%) is operator, with state-owned partner SNPC (25%), and New Age (African Global Energy) Limited (10%). Asia Pacific CNOOC started natural gas production from the Panyu 34-1/35-1/35-2 project at the Pearl River Mouth basin in the South China Sea. Main production facilities for the three gas fields include one comprehensive platform, two sets of underwater production systems, and 13 producing wells. Two wells are producing a total of 21 MMcf/D of gas. The project is expected to reach peak production of 150 MMcf/D.
Africa (Sub-Sahara) Vaalco Energy started oil production from the Etame 12-H development well offshore Gabon. The well was drilled to a measured depth of approximately 3450 m and was targeting the recently discovered lower lobe of the Gamba reservoir. It was brought on line at a rate of 2,000 BOPD with no indication of hydrogen sulfide. Vaalco (28.07%) is the operator with partners Addax Petroleum (31.63%), Sasol (27.75%), Asia Pacific KrisEnergy started drilling the Rossukon-2 exploration well on Block G6/48 in the Gulf of Thailand, using the Key Gibraltar jackup rig. The well will reach a total depth at 5,462 ft and will test Early Miocene stacked fluvial sandstones on a broad structural high. The well will also appraise the Rossukon-1 reservoir, which produced 850 BOPD during tests.
Digital oil fields implementation is ongoing in various oil fields around the world since the last few years. There are many research initiatives focusing on performance improvements trying to eliminate Non-productive time (NPT) caused by equipment failures or drilling conditions but the Invisible Lost Time (ILT), which accumulates when common drilling operations such as drill pipe connections are not carried out efficiently, is neglected. This makes it difficult to compare well delivery time and performance discrepancies for each activity across a field. The main challenge in optimizing drilling performance is deciphering the rich data streams in real time to make informed business decisions. This study focuses on the integration and analysis of real-time drilling data in order to evaluate the drilling performance via Invisible Lost time.
The methodology starts with analysing the effectiveness of the Remote Monitoring (the backbone of Digital Oil Field) of critical drilling operations as the actual performance is compared with predefined operation practices in terms of Rig Performance, Individual Crew Performance and Section Performance over four unknown drilling wells located within Field-X in the North Sea. The Invisible Lost Time is quantified from selected drilling activities such as tripping, drilling, running casing and flat time operations that can result in significant potential savings other than the main drilling operations.
Histograms were utilized to improve rig performance which indicated that the Connection time can lead to significant days’ savings as Tripping time contributes to approximately 60% of the Invisible Lost Time (ILT). Additionally, the effect of various factors such as hole sections and well depth on potential savings was also studied. This strategy may be developed as a cost-effective technology for any drilling or workover wells, as it results in improving drilling key performance indicators (KPI's) leading to performance improvement, risk mitigation and cost efficiency in real-time drilling activities.
Ultrasonic velocities were measured across a variety of samples to link elastic properties with physical properties unique to coals, shaly coals, and coaly mudstones. P- and S-wave velocities have a positive correlation with both rank and inorganic mineral content in coaly rocks from New Zealand. The results compare to previous studies, which show increasing elastic wave speed as a function of organic maturity. In addition, they portray a greater change in elastic moduli (ΔK and ΔG), over increasing coal rank, than velocity (ΔV) or density (Δρ). VP/VS decreases from an average of 2.43 in subbituminous coals to 2.14 in anthracite and continues decreasing with increasing inorganic mineral matter. Further study may elucidate whether these relationships are useful to distinguish coaly rocks in the subsurface through forward modelling or seismic inversion. The comprehensive dataset from this study presents a new geophysical approach towards coaly source rocks. These types of petroleum source rocks are regionally significant, however; they are less common globally.
Fomin, Vitaliy (Halliburton) | Kushmanov, Pavel (Halliburton) | Purwar, Suryansh (Halliburton) | Aksenov, Mikhail (Halliburton) | Durygin, Nikolay (Halliburton) | Golovin, Oleg (Halliburton) | Solovyev, Iliya (IPOS) | Govorkov, Denis (TSOGU) | Vedernikova, Yuliya (TSOGU) | Iskakov, Daulet (TSOGU)
Gas condensate fields present unique challenges regarding data acquisition, data quality, exception-based surveillance, flow modeling, nodal analysis, well testing, allocation, and visualization. Although existing tools and methods address many of these aspects, it is possible to streamline processes and explore increased production efficiency methods. This paper addresses these challenges; it presents a case study of an intelligent control system implementation for a gas-condensate field based on a unified data model, integrated modeling, and cross-domain workflows.
This paper presents a transformative, intelligent, and automated work process, referred to here as "smart workflows." As part of these workflows, virtual gauges are used that are based on inflow models and lifts, adjustable valves, and modular networks. The workflows are implemented on a truly open end-to-end platform that enables the coupling of multiple databases, streamlining of data for an integrated analysis of the measurements and model calculations, and ascertaining the mismatch between the two. The workflows also initialize adaptive self-tuning procedures.
The smart workflows enable engineers to achieve various improvements, including an integrated structure of process data model to enable quick access to validated data, monitoring and control functions to a gas-condensate field in real time, and reduced downtime and operational costs. The smart workflow also supports functions that include collection and verification of measurement data, configuration of the integrated solution component models, evaluation of the action of root causes, and planning of operation scenarios.
As part of the implemented system, an integrated information system data structure sets the degree of relatedness of tasks, each of which can be initialized depending on work situations and/or operator commands.
Such comprehensive analysis of the data provides reliable integrated system configuration parameters of the model, which increases the accuracy of the calculations used in the optimal planning of the operational scenarios.