Initial Gas In Place Research Articles

Integrating seismic attributes, post-stack seismic inversion, and static modeling for assessing the Pliocene-Pleistocene hydrocarbon potentialities, Offshore North Sinai Field, Egypt

Optimal gas production from marginal fields vulnerable to tidal energetic effects is exceedingly challenging. Conventional seismic analysis is insufficient for a significant understanding of the geomorphological description, volumetric calculations, and microfacies analysis of the anticipated heterogeneous gas-bearing sands. New insights into the offshore North Sinai (ONS) Field based on quantitative and geostatistical interpretations integrated with physical and geometrical attribute analyses are boosted for reconstructing diverse-scale reservoir internal architecture.Deterministic band-limited inversion using acoustic impedance logs contributed to the initial knowledge of facies migration during tidal-dominated delta progradation and revealed four 2nd-order sequence boundaries dependent on P-velocity variations with depth as a function of rock elasticity, low impedance gas content of 2500–3000 kPa s/m and overburden compressional factors. Gradual boundaries confining reservoir bases due to spatiotemporal facies discrepancies triggered the implementation of stochastic algorism as a model norm for tracing thin-bedded and internal heterogeneous reservoirs with no predictable gas-water contacts across subtle dismantled areas. Stochastic inversion with intensive layering below −1 ms along with static property reservoir modeling allowed the evaluation of both fine and coarse-scale reservoirs discovered as extensions of injector-controlled stacked mouth bars, fan-lobes, and distributary channels crosscutting tidal mudflats of delta top facies associations within a system of spatially migrated clinoforms to the north. Stream avulsion-induced and accommodation space inconsistencies across syn-sedimentary faults caused the shifting of the Late Plio-Pleistocene clinoform depocenter northward and deltaic facies variation inside each individual sand system, not eustatic sea level fall.After calculating the biogenic gas reserves occupying each reservoir, the present strategy offers an additional seven broad gas prospects within four dismantled blocks, raising the ONS initial gas in place to 967.95 Bcf. In addition, it depicts five gas shoals emplaced at shallow depths, posing considerable drilling hazards. This paper workflow is the first of its kind in the Neogene section of the OSN Basin.

Investigation of methane mass transfer and sorption in Marcellus shale under variable net-stress

Natural gas in shale exists as free and adsorbed gas, subject to prevailing pore pressures and stress conditions. Accordingly, to accurately estimate/predict the shale gas recovery potential, a central requirement is to represent gas transport and sorption behavior under varying stress conditions. The objective of this work is to facilitate the interpretation of laboratory-scale experiments, at relevant conditions, in an attempt to bridge the gap in scales between laboratory- and field-scale observations.We have conducted a series of high-pressure experiments on a full-diameter core sample from the Marcellus shale. These include gas loading (pressure-decay) and depletion (production) experiments with pure methane (CH4) at variable stress conditions to characterize transport and sorption behavior under reservoir-relevant conditions. We have formulated and applied a novel integral model for mass transfer and storage in multi-porosity shale systems that allows us to effectively investigate transport and sorption phenomena: We delineate gas transport by interpreting helium (He) pressure-decay experiments and demonstrate how to use the information gained to calculate the relevant transport coefficients of CH4 and other gases. A separate measurement of the CH4 sorption isotherm on a smaller sample (a shale cube) was interpreted and combined with the transport description to predict the production behavior of CH4 from the experiments with the full-diameter core.Our experiments demonstrate that the representation of sorption hysteresis is crucial for predicting and guiding shale gas production: At the end of both gas production experiments, approximately 20% of the initial gas in place remained in the core. Without accounting for sorption hysteresis, our modeling demonstrates that the CH4 production could be overestimated by 10%. We demonstrate that our integral, triple-porosity model provides an effective approach for the interpretation and prediction of gas transport and sorption behavior during loading and production experiments on shale cores under variable net-stress conditions.In summary, our work combines measurements and modeling of mass transfer and sorption in shales at different scales to validate a characterization approach that facilitates an improved understanding of shale gas production. Furthermore, the triple-porosity model utilized in our work defines a potential pathway for the translation of laboratory-scale experimentation to larger-scale applications.

Petroleum system analysis-conjoined 3D-static reservoir modeling in a 3-way and 4-way dip closure setting: Insights into petroleum geology of fluvio-marine deposits at BED-2 Field (Western Desert, Egypt)

Imperfect determination of petroleum system processes coincidence, entrapment and charge timing, along with reservoir heterogeneity can considerably cause high risks throughout exploration and development phases of petroleum. Therefore, a complete subsurface visualization of the petroleum system nature, elements and processes, is badly required. To this end, we corroborated, in this study, static reservoir modeling with petroleum system analysis workflows, to better characterize the Cenomanian fluvio-marine reservoir, sandstones of Bahariya Formation, at Bed-2 Field, Abu Gharadig basin (Western Desert, Egypt). We used dataset of 2D seismic profiles and well logs of eight wells. The geometry and property of the reservoir were acquired performing static reservoir geocellular modeling approach. The geohistory, timing of charge, migration pathways, and accumulation sites were identified performing 1D and 2D basin modeling approaches. Combining both approaches was aimed at identifying new petroleum prospect areas, and estimating the hydrocarbon volumes, that are the need for such poorly-defined petroleum systems area. As indicated by the constructed, robust, reservoir and 1D-2D basin models, an additional hydrocarbon prospect, to the north central part of Bed-2 Field, is proposed to be drilled during the further oilfield development phases of the area. This prospect has all features that adequately lead to reliable inferences regarding the ultimate petroleum potential of the area. • Reservoir modeling delineating geometry and property, with depositional facies analysis unlocking reservoir heterogeneity • Petroleum system analysis workflow defining the hydrocarbon charge timing, confirming the hydrocarbon potential of the area • Pixel-based stochastic simulation algorithms modeling the rock property. • Hydrocarbon volumes assessment, gas initially in place (GIIP) and stock-tank oil initially in place (STOIIP), in the area • Defining new prospect areas, justifying future oilfield development plans

Assessment of prospective gas resources and develop a production view of eastern foldbelt (block 18), Bangladesh using Monte Carlo simulation method

In Bangladesh, 20 gas fields out of 28 produced 709.11 billion cubic feet (Bcf) through 112 wells against a vast amount of demand in the financial year 2021–22. Therefore, more gas fields need to be explored in the most prospective offshore part of Bangladesh. In this study, we have attempted to estimate a prospecting natural gas reserve in the Eastern Fold Belt (Block 18) consisting of Teknaf, Coral Dip, and St Martin Island as well as to develop a production view for the future. Based on the prerequisite research data collected from Petrobangla, Monte Carlo simulations were used to estimate the reserve values as Gas Initially In Place (GIIP) and Recoverable Gas Initially In Place (RGIIP) by Petroleum Engineering (PE) Essential software (version 2017.4). The results show that the estimated GIIP and RGIIP are 6145.88 billion standard cubic feet (Bscf) and 4745.5 Bscf, respectively which are quite close to the previous study. The total estimated proven natural gas of the study is 2064.4 Bcf.

A new approach to production data analysis of non-volumetric naturally fractured gas condensate reservoirs

A significant amount of hydrocarbon exists in naturally fractured formations. Due to the limitations of classical reservoir evaluation methods, the ongoing researches have focused on the analysis of production data to describe reservoir dynamic. Among the existing methods, the flowing material balance (FMB) technique brings a straightforward and accurate method of reserve estimation. Often, the same approach as the single porosity reservoirs are utilized for naturally fractured formations and fewer studies have been performed with the dual-porosity model. Regarding the importance of such reservoir types, the purpose of this study is to propose a new production data analysis approach by implication of a modified compressibility parameter to the conventional FMB equations to achieve an accurate estimation of initial gas in place and average reservoir pressure in non-volumetric naturally fractured gas condensate reservoir. In the current study, we applied the aquifer influence on reservoir performance in the FMB equation by a modified isothermal rock compressibility factor, without using complex multi-phase reservoir modeling. Due to inherent uncertainty associated with aquifer parameters, the production data analysis in this study proceeded in two phases. In the first phase with the assumption of known aquifer parameters, output data were obtained. In the second phase, based on the best-fitted aquifer parameters in advance, the impact of variation of aquifer input data on the validity of output results was studied using the Monte-Carlo simulation approach. To validate the proposed method, different simulation models with variable reservoir and fluid properties were defined and the results were compared against a commercial compositional simulator. The obtained results proved the accuracy of the proposed method. Therefore, applying the modified rock compressibility in the conventional FMB method would result in a simple yet accurate method that requires the least input data to estimate initial gas in place and average reservoir pressure.

The Application of P/Z Methods in Evaluation of Initial Gas in Place of X Reservoir

Reservoir X is located in West Tanjung Jabung Regency, Jambi, Indonesia, with initial pressure is 2,028 psia, and a temperature is 226°F. The reservoir has been produced from February 2018 to the present (February 2021), with cumulative gas production of 5.17 Bscf. Based on the Plan Of Development (POD) study in 2016, the initial gas in place was determined volumetrically to be 49,92 Bscf. To compare the initial gas in place, it is deemed necessary to recalculate the initial gas in place by utilizing another method. The calculation of Initial Gas In Place (IGIP) is conducted by using the P/Z method. In this method, the Initial Gas in Place is obtained 49.01 Bscf. Based on analyzing the phase diagrams and the prevailing reservoir conditions, reservoir X indicated a dry gas reservoir. Such reservoir drive mechanism is a depletion drive, determined from the P/Z vs Gp plot, generating a straight line. Based on the assumed abandonment pressure value of 300 psia, the estimated ultimate recovery value is 41.93 Bscf, with the recovery factor value of 87.65% and the remaining reserves of 36.76 Bscf.

The influence of adsorption layer thickness and pore geometry on gas production from tight compressible shales

In tight shales, gas is stored in both free and adsorbed form. A one-dimensional model is derived for shale gas production by pressure depletion where the adsorbed layer thickness is of similar magnitude as the pore radius and can affect flow performance. The adsorbed layer thickness is a function of pressure. Different pore geometries are assumed varying continuously between spherical pores to more fracture shaped pores. The shale is assumed compressible and its porosity and pore radius reduce with pressure depletion. The effective pore radius (pore radius minus adsorption layer thickness) controls intrinsic and apparent permeability. The impact of the adsorption layer, compressibility and geometry are investigated. A given adsorbed layer thickness fills more of the pores when they are more spherical and concentrates more of the volumetric flow to the effective pore boundaries giving lower permeability for a given effective radius. Increasing the adsorbed thickness increases the adsorbed fraction initial gas in place. A high volume fraction adsorbed gas reduces apparent permeability and delays production. Pressure depletion causes both pore radius and adsorbed layer to be reduced. The change in adsorbed layer thickness is low at high pressure and greater at low pressure, while pore radius changes more linearly and more with higher compressibility. The free gas saturation and slip increases with pressure depletion for low compressible cases, but if matrix compression dominates there can be a net reduced permeability. Recovery was linear with the square root of time for all cases. Adsorbed gas is less effectively produced by pressure depletion than free gas and higher adsorbed content by more spherical pores or higher layer thickness reduces end recovery. Higher compressibility reduces permeability and delays recovery but increases end recovery. Higher compressibility reduces permeability and delays recovery but increases end recovery. Cited as: Abolghasemi, E., Andersen, P.Ø. The influence of adsorption layer thickness and pore geometry on gas production from tight compressible shales. Advances in Geo-Energy Research, 2021, 6(1): 4-22. https://doi.org/10.46690/ager.2022.01.02

RESERVOIR PERFORMANCE ANALYSIS USING MATERIAL BALANCE METHOD IN GAS FIELD

The RF reservoir is a dry gas reservoir located in Northeast java offshore that has been produced since 2018. The RF reservoir has produced 2 wells with cumulative production until December 2019 is 31.83 BSCF. In January 2018 the gas production rate from the two wells was 36 MMSCFD and the reservoir pressure at the beginning of production was 2449.5 psia, peak production occurred in April 2019 with a gas flow rate of 98 MMSCFD but in December 2019 the gas production rate from both wells decreased to 30 MMSCFD with reservoir pressure decreased to 1607.8 psia. Changes in gas flow rate and pressure in the RF reservoir will affect changes in reservoir performance, so it is necessary to analyze reservoir performance to determine reservoir performance in the future with the material balance method. Based on the results the initial gas in place (IGIP) is 80.08 BSCF. The drive mechanism worked on the RF reservoir until December 2019 was a depletion drive with a recovery factor up to 88% and a current recovery factor (CRF) is 40%. The remaining gas reserves in December 2019 is 39 BSCF and the reservoir will be made a production prediction until December 2032. Based on production predictions of the four scenarios, scenario 2 was chosen as the best scenario to develop the RF reservoir with a cumulative production is 66.1 BSCF and a recovery factor of 82.6%.

Petrophysical evaluation of sandstone gas reservoir using integrated well logs and core data for the Lower Cretaceous Kharita formation, Western Desert, Egypt

This study aims to evaluate Kharita gas reservoir to enhance the production. The increase in water-cut ratio reduces the left hydrocarbons’ amount behind pipe. Accurate determination of pore throats, pores connectivity and fluid distribution are central elements in improved reservoir description. The integration of core and logging data responses is often used to draw inferences about lithology, depositional sequences, facies, and fluid content. These inferences are based on petrophysical models utilizing correlations among tools’ responses as well as rocks and fluids properties. Upper Kharita Formation produces gas and condensate from the clastic sandstone in Badr-3 field, western desert of Egypt. It consists mainly of sandstone with shale intercalations. It is subdivided into three sub-units Kharita A, Kharita B and Kharita C that are in pressure communication. Hence, a new further investigation and review for the previously calculated GIIP (gas initially in place) was initiated. The results of this study yielded that the main uncertainty in the volumetric calculations was the petrophysical evaluation; subsequently, a new unconventional petrophysical evaluation approach was performed. The sands thickness in Upper Kharita Formation varies between more than 9 up and more than 61 m with average porosity values range between 0.08 and 0.17 PU while the average permeability values range between 1.89 and 696.66 mD. The average hydrocarbon saturation values range between 46 and 97%. The sands thickness in Upper Kharita Formation varies between more than 9 up and more than 61 m with average porosity values range between 0.08 and 0.17 PU while the average permeability values range between 1.89 and 696.66 mD. The average hydrocarbon saturation values range between 46 and 97%. Reservoir shale cutoff of 55% by using cross-plot between shale volume and porosity (Toby Darling concept) was utilized to discriminate the reservoir from non-reservoir sections. The porosity model was used to calculate reservoir porosity, using the density log. The Archie and saturation/height function models were used to calculate the water saturation and used to calibrate the water saturation in the transition zone. The porosity–permeability (POR-PERM) transform equation was used to estimate the reservoir connectivity (absolute permeability) for the four petrophysical facies (High Quality Reservoir, Moderate Quality Reservoir, Low Quality Reservoir and Highly Shale Reservoir). Core data have shown variations in reservoir quality parameters (porosity and permeability) from one well to the other. Integration of all the reservoir pressures indicated that there are different fluid types (oil, gas and water) in the Upper Kharita Formation level. The saturation/height function model was used to calibrate the saturation in the transition zone. The integration of geological core and geophysical log data helped to conduct a comprehensive petrophysical assessment of Upper Kharita Formation for a better estimation of the reservoir and to achieve a better understanding of the water encroachment in the Upper Kharita reservoir. The big challenge is the determination of the most correct model for calculating porosity, permeability and water saturation in this reservoir of different quality sand. The new petrophysical evaluation resulted in doubling the volumes in Upper Kharita reservoir and so a perforation campaign was performed to confirm the new volumetric calculations, which showed a good match with the model results. Hence, a new well was drilled targeting the low quality sand and found them with high pressure almost near virgin pressure.

Seismic Attribute Analysis and 3D Model-Based Approach to Reservoir Characterization of “KO” Field, Niger Delta

Modelling involves the use of statistical techniques or analogy data to infill the inter-well volume producing images of the subsurface. Integration of available data sets from “KO” field were used to identify hydrocarbon prospects and by means of interpolation, populate the facies and petrophysical distribution across the field to define the reservoir properties for regions with missing logging data[KO1] . 3D seismic data, check-shot data, and a series of well logs of four wells were analyzed, and the analysis of the well logs was performed using the well data. The synthetic seismogram produced from the well ties [M.N.2] [KO3] was used to map horizon slices across the reservoir regions. Four horizons and fifteen faults, including one growth fault, four major faults, and other minor faults, all in the time domain were mapped. Attribute analyses were carried out, and a 3D static model comprised of the data from the isochore maps, faults, horizons, seismic attributes, and the various logs generated was built. A stochastic method was also employed in populating the facies and petrophysical models. Two hydrocarbon-bearing sands (reservoirs S1 and S2) with depth values ranging from –1729 to 1929 m were mapped. The petrophysical analysis gave porosity values ranging from 0.18 to 0.24 across the reservoirs, and the permeability values ranged from 2790 to 5651 mD. The water saturation (Sw) of the reservoirs had an average value of 50% in reservoir S1 and 47% in reservoir S2. The depth structure maps generated showed an anticlinal structure in the center of the surfaces, and the mapped faults with the four wells were located in the anticlinal structure. The reserve estimate for the stock tank oil initially in place (STOIIP) of the reservoirs was about 70 mmbbl, and the gas initially in place (GIIP) of the reservoirs ranged from 26714 to 63294 mmcf. The result of the petrophysical analysis revealed the presence of hydrocarbon at favorable quantities in the wells, while the model showed the distribution of these petrophysical parameters across the reservoirs. Modelling involves the use of statistical techniques or analogy data to infill the inter-well volume producing images of the subsurface. Integration of available data sets from “KO” field were used to identify hydrocarbon prospects and by means of interpolation, populate the facies and petrophysical distribution across the field to define the reservoir properties for regions with missing logging data[KO1] . 3D seismic data, check-shot data, and a series of well logs of four wells were analyzed, and the analysis of the well logs was performed using the well data. The synthetic seismogram produced from the well ties [M.N.2] [KO3] was used to map horizon slices across the reservoir regions. Four horizons and fifteen faults, including one growth fault, four major faults, and other minor faults, all in the time domain were mapped. Attribute analyses were carried out, and a 3D static model comprised of the data from the isochore maps, faults, horizons, seismic attributes, and the various logs generated was built. A stochastic method was also employed in populating the facies and petrophysical models. Two hydrocarbon-bearing sands (reservoirs S1 and S2) with depth values ranging from –1729 to 1929 m were mapped. The petrophysical analysis gave porosity values ranging from 0.18 to 0.24 across the reservoirs, and the permeability values ranged from 2790 to 5651 mD. The water saturation (Sw) of the reservoirs had an average value of 50% in reservoir S1 and 47% in reservoir S2. The depth structure maps generated showed an anticlinal structure in the center of the surfaces, and the mapped faults with the four wells were located in the anticlinal structure. The reserve estimate for the stock tank oil initially in place (STOIIP) of the reservoirs was about 70 mmbbl, and the gas initially in place (GIIP) of the reservoirs ranged from 26714 to 63294 mmcf. The result of the petrophysical analysis revealed the presence of hydrocarbon at favorable quantities in the wells, while the model showed the distribution of these petrophysical parameters across the reservoirs. [KO1]Sentence has been rephrased. [M.N.2]This verb does not make sense in this context and has made the sentence unclear. [KO3]Sentence has been rephrased

Special features of tight gas reserves determination

Special features of tight gas reserves determination, based on material balance method, were characterized, since reliability of initial hydrocarbons in place determination plays important role in future field development planning, particularly on recovery rate, wells to be drilled, capital expenditures, surface facilities etc. Using the synthetic 3D model of gas reservoir, different development scenarios were evaluated according to the different spatial distribution patterns of petrophysical properties within the reservoir. Analyzing the obtained results, the authors fully confirmed an assumption made, that significant heterogeneity of reservoir properties makes a great impact on the shape of pseudo reservoir pressure curve vs cumulative gas produced and introduces significant errors into determination of initial gas in place. At the late stages of the development, the slope of P/z straight line changes, and this allows determination of much greater reserves’ volumes. Usage of pseudo reservoir pressure vs cumulative produced gas for determination of drained reserves in tight gas formation is especially risky, because the production data can indicate the true volumes of gas in place, only after the majority of the gas been produced. In most cases, the development period to acquire necessary data for correct volumes in place estimation exceeds the planning period. This factor introduces the significant error into future field development during the planning phase. Due to that, at the initial development stages, the error in drained volumes estimation can account for 50% out of true initial volumes in place. Based on conducted research, the potential error evaluation for tight gas reservoirs initial gas in place determination with decline pressure material balance method was performed. According to the results of computer simulation, the error can account for 25% from true initial gas in place in simulation model. This error significantly excesses the acceptable limits and can lead to wrong decisions in development planning

EVALUASI ISI AWAL GAS DI TEMPAT DAN ANALISIS DECLINE CURVE PADA RESERVOIR YS

YS reservoir has data of gas initial in place (GIIP) with a volumetric method of 3,476 Bscf. Because of improvement of data, GIIP can be evaluated using material balance method. Then the production of wet gas will be forcasted with plateu rate of 40 Mscf/d. The PVT data that needs to be calculated in this study is the gas and water compressibility factor and the formation volume factor each year. In determining the type of drive mechanism, a plot of P / Z versus cumulative gas production is carried out, from the analysis, the type of drive mechanism is water drive, it is necessary to calculate the water influx, the method used is the Van Everdengen-Hurst method. After all the required parameters are available, the calculation of the initial gas in place will be calculated, the method used is the material balance method and the straight line material balance method. The results of the initial gas in place calculation using the material balance and straight line material balance methods are 3,430 Bscf and 3,428 Bscf. If the results of the material balance method and the straight line material balance method are compared with available GIIP volumetric method data, the percent difference is 1,32% and 1,37%. It can be said that GIIP result using the material balance method and the straight line material balance method is accurate because after being evaluated using volumetric method, it only has a small percentage difference. Then from calculation, recovery factor are 67,43% using gas initial in place of straight line material balance method. With remaining reserve of 16,532 MMscf, the time of production plateu with 40 Mscf/d is 12,40 months.

Vaux-en-Bugey (Ain, France): the first gas field produced in France, providing learning lessons for natural hydrogen in the sub-surface?

The former Vaux-en-Bugey field, first French methane production from early 20th century, is revisited as a case study to address the present generation and accumulation theories for gases like hydrogen and helium. The volume of the initial gas in place is estimated to be 22 million m3. Based on a composition of 5% of hydrogen and 0.096% of helium, the volumes of these gases in the field were respectively around 1.1 million m3for hydrogen and 24 000 m3for helium. The different hypotheses of hydrogen sources are reviewed: serpentinization, hydro-oxidation of siderite, water radiolysis, bio-fermentation, mechanical generation, degassing from depth trough faults, steel corrosion. For helium generation, the different sources of radioactive minerals and intermediate accumulations are examined. The most probable scenario is the hydrogen production by water radiolysis and helium production by radioactive decay in or near the basement, migrating trough deep faults, stored and concentrating in an aquifer with thermogenic methane, then flushed by methane into the gas field, during Jura thrusting. New measurements with portable gas detector, incomplete but including hydrogen, on a former exploration well with accessible flux of gas, give the opportunity to comment gas saturation evolution more than a century after the 1906 discovery. The decreasing of hydrogen content since the discovery of the field is probably due to Sulphate-Reducing Bacteria activity.

The Goldeneye Field, Blocks 14/29a and 20/4b, UK North Sea

Abstract The Goldeneye gas-condensate field lies in the Moray Firth Basin in the UK Continental Shelf (UKCS) approximately 100 km off the NE coast of Scotland. The field was discovered in 1996 as a normally pressured accumulation with estimated gas-initially-in-place (GIIP) of 810 bcf with a thin oil rim in the Lower Cretaceous Captain Sandstone Member in a three-way, dip-closed structure. Field development included five production wells, with first gas achieved in 2004. Goldeneye was steadily produced under moderate aquifer support until cessation of production (COP) in 2010 following water breakthrough at the wells. Over its lifetime Goldeneye has produced 568 bcf of gas and 23 MMbbl of condensate. Around the time of COP, the UK Carbon Capture and Storage Commercialisation Competition was announced, and Goldeneye was evaluated as a candidate. The removal of significant volumes of hydrocarbons through production left remaining capacity that could be refilled without reservoir pressure significantly exceeding virgin conditions. However, following withdrawal of funding from the UK Government in 2015, the project was put on hold. Since then additional subsurface work has been conducted to support the successful abandonment of the development wells, which had previously been suspended since 2010.

Comparison of gas initial in place calculation using MBAL and Artificial Intelligence methods

Oil and gas industry are an industry with a high cost and high risk, artificial intelligence will help the work of humans to minimize the risk of accidents, reduce processing time and improve corporate profits. So, the work becomes more efficient. The aims of the study give information that the artificial intelligence help the work to evaluate the initial gas in place on reservoir and comparison the results between software and manual Material Balance (MBAL). Additional research is needed to know the type of reservoir and drive mechanism. The method used is the research on reservoir RGN, the data used are based on real data in field. This research uses artificial intelligence MBAL software and calculation with manual MBAL. Based on the analysis, the result of reservoir type dry gas reservoir with drive mechanism is depletion drive. Calculation initial gas in place using artificial intelligence MBAL software, get the initial gas in place result of 50661,3MMscf. And calculation using manual MBAL, get the initial gas in place result of 50063,59MMscf. There is a difference in the results of the initial gas content in place of 597.4 MMscf. Based on the analysis, there are differences in the results between using artificial intelligence and manual MBAL.

Reserve evaluation of high pressure and ultra-high pressure reservoirs with power function material balance method

It is difficult to determine the effective reservoir rock compressibility, aquifer volume and water influx of high pressure and ultra-high pressure gas reservoirs, so when the traditional apparent reservoir pressure and cumulative gas production curve extrapolation method and its modified version are used to calculate the initial gas in-place of such gas reservoirs, the calculation accuracy is lower. The material balance equation in the form of power function for such gas reservoirs was established based on Gonzalez method to improve the accuracy and reliability of reserve evaluation. Then, based on 20 high pressure and ultra-high pressure reservoirs that had been developed abroad, the empirical value of the power exponent was defined, and the influences of the depletion degree of apparent reservoir pressure and the degree of reserve recovery on the reliability of reserve calculation were analyzed. Besides, the critical value of the key parameter affecting the reliability of reserve evaluation (depletion degree of apparent reservoir pressure) was determined and compared with the critical value of the two-linear trends. Finally, an example calculation was carried out. And the following research results were obtained. First, the empirical value of the power exponent calculated using the material balance method in the form of power function is 1.02847, with an upper limit of 1.11567. Second, the depletion degree of apparent reservoir pressure corresponding to the inflection point of the classical two-linear trends ranges from 0.14 to 0.38 with an average of 0.23, while that corresponding to the extrapolation point of the second straight line is between 0.23 and 0.50 with an average of 0.33, and the corresponding degree of reserve recovery is in the range of 33%–65% with an average of 45%. Third, the reserves of such high pressure gas reservoirs calculated with this new method has an error rate less than 10% if the depletion degree of apparent reservoir pressure is greater than 0.33. In conclusion, for such high pressure gas reservoirs and the stress-sensitive fractured gas reservoirs, the material balance method in the form of power function proposed in this paper can avoid the uncertainty parameters (e.g. effective reservoir rock compressibility, aquifer volume and water influx) and it is advantageous with simple calculation process, better practicability and small error.

Application of Ensemble Variance Analysis in the Development of the Wheatstone Field Startup Strategy

Summary Starting initial field production is a unique opportunity to acquire reservoir–surveillance information that can impact future reservoir performance. When a field is perturbed by first production, there is the potential to reduce uncertainty in reservoir properties by monitoring the pressure changes at nonproducing wells with downhole pressure gauges and comparing the observed signal with a range of simulation–model results. The Wheatstone Field, located offshore of Northwest Australia, recently began production startup to supply gas to the Wheatstone liquefied–natural–gas (LNG) facility. The operational guidelines required each development well to start with a single–well–cleanup flow to the Wheatstone platform. The initial single–well–cleanup flows of the Wheatstone field provided scope for selecting a well flow sequence with observation at nonproducing wells. The recommended sequence of initial cleanup flows was designed with a focus on reducing reservoir uncertainties by means of ensemble variance analysis (EVA). EVA is a statistical correlation technique that compares the covariance between two sets of output data with the same set of inputs. For the Wheatstone Field well–cleanup flow sequence selection, the EVA workflow compared the full–field design of experiments (DoE) study of field depletion and a series of short early–production reservoir–simulation DoE studies of the gas field. The covariance between the two DoE studies was evaluated. The objective of the EVA approach was to determine the startup sequence that would allow for the best opportunity to reduce subsurface uncertainty. This objective was met by ranking multiple cleanup flow sequence scenarios. The key factors considered for sequence selection ranking were the impact on business objectives, such as future–drilling–campaign timing and location of infill wells, and insights on reservoir connectivity, gas initially in place (GIIP), and permeability. The recommended sequence of well–cleanup flows uses a superpositioned pressure signal to boost response at observation wells, which improves measurement resolvability. The selected sequence preserves key observation wells for each manifold and reservoir section for as long as possible before those wells are required to be flowed to meet operational requirements. Operational constraints and variations of the startup plan were considered part of the evaluation.

EVALUASI ISI AWAL GAS DI TEMPAT DAN ANALISIS DECLINE CURVE PADA RESERVOIR YS

YS reservoir has data of gas initial in place (GIIP) with a volumetric method of 3,476 Bscf. Because of improvement of data, GIIP can be evaluated using material balance method. Then the production of wet gas will be forcasted until below economic limit. The PVT data that needs to be calculated in this study is the gas and water compressibility factor and the formation volume factor each year. In determining the type of drive mechanism, a plot of P / Z versus cumulative gas production is carried out, from the analysis, the type of drive mechanism is water drive, it is necessary to calculate the water influx, the method used is the Van Everdengen-Hurst method. After all the required parameters are available, the calculation of the initial gas in place will be calculated, the method used is the material balance method and the straight line material balance method. The results of the initial gas in place calculation using the material balance and straight line material balance methods are 3,430 Bscf and 3,428 Bscf. If the results of the material balance method and the straight line material balance method are compared with available GIIP volumetric method data, the percent difference is 1,32% and 1,37%. It can be said that GIIP result using the material balance method and the straight line material balance method is accurate because after being evaluated using volumetric method, it only has a small percentage difference. Then from the decline curve and Trial Error and X2 – Chisquare Test analysis, the decline curve is exponential with Di at 1,103 / month. After forecasting until production of wet gas is below the economic flow rate of 0,045 Mscf / d, it is known that the productive age is until 1st September 2021 with the values of EUR and RR respectively 2,309 and 0,014 Bscf. Using the results of GIIP using the material balance and straight line method, the current recovery factor are 67,34% and 67,37 %.

Researches on calculation methods of aquifer influx for gas reservoirs with aquifer support

Abstract The existence of aquifers in gas reservoirs has important influences on the development of gas wells. Water will invade into gas reservoirs when formation pressure decreases during the production of a gas well and then change the well production characteristics severely. It is very important to research the aquifer invasion mechanisms and evaluate the aquifer influx for good knowing and exploring the gas reservoir. In this paper, we have conducted three methods to research the aquifer influx characteristics by evaluating the value of aquifer influx and aquifer influx rate that vary with the production time. Three methods are the Blasingame method, the FMB (Flowing Material Balance) method and the MBE (Material Balance Equation) method. Based on the Blasingame conventional type-curves, the normalized well production data of a gas well influenced by aquifers can be divided into three influx periods: no-aquifer, early-aquifer and middle-late-aquifer influx period. The no-aquifer influx period production data are used to determine well initial gas in place and as a base, and the early-aquifer influx period production data are used to obtain aquifer influx and aquifer influx rate quantitatively. The novel three methods presented can elucidate the aquifer influx characteristics clearly and determine aquifer influx rate quantitatively just using well dynamic production data based on the Fetkovich model. Meanwhile, a simple numerical simulation model was built to verify the three methods, which shows that these three methods are reliable and really have strong practicability in developing gas field reservoirs with aquifer support.

Reserve Estimation Technique for Low Permeability Shale Gas Formations of Lower Indus Basin, Using Simulation Approach

Produced Natural Gas from the low permeability tight shale reservoirs are called as Shale Gas, has a great importance in economic terms of supply and demand because of natural gas prices. Shale is composed of a rock having sedimentary of clastic nature that contains mudstone and siltstone under the specific reservoir conditions of pressure and temperature are called Shale gas. Shales are of the soft nature formation that formed due to pre-existing rocks which have been elated, worn out and transported into a new form of rock. Shale is found in reservoir rock where organic material migrated upward and in areas where conventional clays are normally present. Shale is known as unconventional energy source. Due to high demand in population rate and increasing consumption of natural gas in transportation sector it is challenging for Pakistan to meet the energy requirements and needs in utilizing both conventional and unconventional energy resources. In this research study, the set of data, tools and methodology applied to estimate initial gas in place (IGIP), recoverable reserves, recovery factor, and risk analysis of shale gas reservoirs. The study reveals potential and characteristics of shale reservoir to grade the areas in term of shale thickness, its hydrocarbon generation potential, current depth and maturity for shale gas exploitation.