Drill Stem Test Research Articles

Field Features Do Not Explain Greenfield Production Forecasting Bias

Summary Over the past years, it has become clear that greenfield oil production forecasts are subject to strong optimism and overprecision biases: Significant early production shortfalls are the rule rather than the exception and the elicited uncertainty range is generally too narrow. This has large negative consequences for the net present valuation of such investments. A study from 2011 based on post-factum evaluation of greenfield production forecasts suggests that there is a causal relationship between certain project/field characteristics and production attainment (i.e., optimism bias). However, while self-reported causes of failure may provide interesting insights, such analyses are subject to cognitive hindsight bias. It is therefore necessary to test such claims more rigorously. Research on megaprojects in other industries suggests that forecasting bias is omnipresent but is stronger in certain circumstances (e.g., information and communication technology projects are subject to larger cost overruns than road construction projects). An important question is therefore whether there are combinations of field characteristics/features which can be measured objectively, such as field size, reservoir complexity, oil prices, and lack of drillstem tests (DSTs), etc., and which can be shown to have predictive power of overly optimistic and overconfident production forecasts. The data set in this study consists of 71 greenfield oil production forecasts at project sanction on the Norwegian Continental Shelf (NCS), with production starting between 1995 and 2020. Each forecast consists of a triplet of production curves which represent the statistical p10, the expectation, and the statistical p90. The forecasts are compared with actual production data. Metadata about the fields gathered from the Norwegian Petroleum Directorate (NPD) are used to establish 16 informative field features, from field reserves to the number of appraisal wells per unit area. These features are tested for predictive power, both individually and simultaneously, of optimism bias and of a general forecast quality metric. First, we show that value erosion caused by time overruns and production shortfalls are both significant, but that the relative importance of effects after production start is higher. Second, none of the tested machine learning models show any predictive power of forecasting bias. Because of this systematic presence of bias in the production forecasts, we argue that oil and gas companies need to make important changes to their decision-making workflows to take into account well-documented research findings on cognitive and organizational bias from the past decades, instead of the ever-increasing model complexity. Illustratively, as a final point, we show that a no-skills-involved reference class forecast based on empirical production curves from abandoned fields outperforms operators’ own greenfield forecasts. This approach may perhaps serve as a useful benchmark for future forecasts.

Shallow Overpressure Formation in the Deep Water Area of the Qiongdongnan Basin, China

The scarcity of drilling in the deep water area of Qiongdongnan Basin restricts the cognition and prediction of overpressure. In this paper, a shallow zone of overpressure at the depth of 900–1,200 m below the sea floor in the deep water area was found by analyzing electronic logs, mud pressure (Mud pressure is a product of the height of the column of mud, density and gravity acceleration) and test pressure from drill stem testing (DST) and modular dynamic testing (MDT), and the interpretation of anomalous seismic interval velocities. The shallow overpressure is a newly observed geological phenomenon in the South China Sea for which the generation mechanisms are not well understood, despite similar observations and analyses elsewhere in the world. Two representative wells, one each located in the shallow water and the deep water areas, respectively were selected to investigate the vertical distribution of the shallow overpressure. The top of the overpressure in Well A in the shallow water area is about 2,111 m below sea floor, while the top of the overpressure in Well B in the deep water area is about 1,077 m below sea floor. A pressure coefficient (i.e., ratio of pore pressure to the normal hydrostatic pressure measured from the sea surface) profile was constructed from the shallow water area to the deep water area using the calibrated relationship between seismic interval velocities and pressure data from 30 wells. The distance between the top of the overpressure and the seabed is predicted to be between 900 and 1,200 m in the deep water area Basin. Disequilibrium compaction is the interpreted primary cause of the shallow overpressure and the results of basin modeling indicate that the shallow overpressure was generated since 5.5 Ma.

Natural fractures in the deep Sinian carbonates of the central Sichuan Basin, China: Implications for reservoir quality

The deeply buried carbonates in the Sinian Dengying Formation are one of the crucial hydrocarbon exploration targets in the central Sichuan Basin of China, and are characterized by strong heterogeneity in reservoir quality, which is closely related to natural fractures. To reveal the impacts of natural fractures on the reservoir quality of Deng-4 Member carbonates in the Gaoshiti-Moxi area, the types, characteristics, and factors controlling the development and effectiveness of fractures, were systematically analyzed based on core samples, thin sections, image logs, petrophysical measurements, and drill stem tests. Tectonic shear fractures are the dominant fracture type affecting the petrophysical properties of the Deng-4 Member reservoirs. The distribution and development of shear fractures are mainly controlled by lithology, mechanical layers and faults. Factors influencing the effectiveness of shear fractures include the timing of fracture formation, cementation, dissolution and current in-situ stress. Early-formed shear fractures are more susceptible to filling during subsequent cementation, whereas fractures formed at later stages are rarely filled and, also, have the potential to be solution-enlarged by dissolution. The relatively large apertures of unfilled shear fractures parallel to the orientation of SHmax are associated with the small effective normal stress exerted on fracture surfaces. Shear fractures effectively improve the overall permeability of Deng-4 Member carbonate reservoirs by connecting relatively isolated pores but have only minor impacts on reservoir porosity. The development degree and effectiveness of fractures together determine the contribution of fractures to reservoir permeability. In the Gaoshiti-Moxi area, shear fractures in the NWW-SEE and nearly E-W strikes provide the major flow pathways and contribute the most of permeability of the tight carbonate reservoirs in Deng-4 Member. These results provide insights for deeper understanding of the impact on reservoir quality of natural fractures in tight carbonates, and are significant for the evaluation of high-quality carbonate reservoirs in the Sichuan Basin.

A Numerical Evaluation of Coal Seam Permeability Derived from Borehole Gas Flow Rate

Coal seam permeability is a critical factor in coal seam gas extraction and gas outburst control. In Australian coal mines, coal seam permeability is normally estimated using a packer test or drill stem test. In contrast, Chinese coal mines generally estimate a parameter called the “gas conductivity coefficient” by measuring natural gas flow rates from an underground borehole drilled through a coal seam. With this method, it has been frequently reported that the permeability of many Chinese coal seams is between 0.0001 mD and 0.01 mD, which is extremely low compared to that of Australian coal seams (1–100 mD). It is therefore natural to wonder how closely the Chinese method measures permeability. Resolving this question will allow knowledge and experience in outburst management to be shared between Australian and Chinese coal mines. This question is investigated by the numerical modelling of gas desorption and flow through a seam of known permeability and by using the model’s borehole gas flow rate to estimate the permeability using the Chinese method. A total of 126 simulations were run with various input reservoir parameters. The results suggest that the Chinese method estimates permeability at an accuracy of 85% to 100%, which is adequate for mine pre-drainage design and outburst control. For the high diffusion rate (e.g., high gas content and short desorption time) and low Darcy flow rates (e.g., low permeability), these errors are reduced.

Nonlinear seismic inversion by physics-informed Caianiello convolutional neural networks for overpressure prediction of source rocks in the offshore Xihu depression, East China

Pressure prediction has long been one of subject of research focuses in petroleum geology and exploration, but is traditionally limited to moderately overpressured formations due to disequilibrium compaction based on the empirical velocity-pressure model. Overpressures in the Xihu depression are caused by fluid expansion due to the generation of natural gas in source rocks. The resulting abnormally pressured gas reservoirs manifest as a high-pressure structure with the thick mud-coated thin sand (MCS) that remains largely unaddressed in prediction. Such gas-producing overpressures make traditional prediction methods unapplicable because of the significant influence of high gas contents on seismic velocities. We employ a frequency-dependent quality factor Q–pressure petrophysical model because of the sensitivity of acoustic attenuation to overpressures. However, acoustic attenuations from rock physics and sonic logging present an uncertain dependence on pore pressures. This implies that overpressure prediction is a typical physical system that is characterized by both deterministic mechanism and statistical behavior, which resorts to physics-informed deep learning methods. We take the Q–pressure petrophysical model as the activation function of Caianiello convolutional neurons with an attempt to combine deterministic and statistical mechanisms for overpressure prediction. Such convolutional neurons render strong feature extraction and powerful learning ability and are used to construct physics-informed Caianiello convolutional neural networks (CCNNs) for overpressure prediction in the Xihu depression. The comprehensive CCNNs-based seismic inversion scheme for overpressures consists of reservoir petrophysical modeling, deep learning for neural wavelets, well-seismic correlation analysis, deconvolution-based inversion for an initial pressure model, and input-signal reconstruction to improve the initial pressure model. With drill stem tests (DSTs), well logs, and 3D seismic data, we conduct the overpressure prediction associated with cross validation in the Xihu depression, which demonstrates the applicability of the physics-informed CCNNs inversion scheme. Predicting reliability away from the training wells usually depends on the geological complexity of areas under study. Nevertheless, the information representation in the trained CCNNs can be improved gradually by feeding new well data during the development of an oil field.

Dst Data Evaluation In Practice

Originally Drill Stem Test (DST), as an evaluation tool, was only an indicator of type of fluid production. Interest in the DST as a modern evaluation tool was revived when certain theoretical equations were proven as a means of calculating values for important formation parameters. This paper is an example, the basic interpretation method, that will prepare the geologist and engineer for more sophisticated approaches that are sure to come, It is proposed of this paper to show how DST data might be Ned to make certain reservoir parameter de- terminations, in field works.

Production Strategy Calls for Injection of High-Gas/Oil-Ratio HP/HT Crude

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 203484, “The Innovative Production Enhancement Strategy of Using High-GOR Crude in HP/HT Reservoir To Lift Upper Reservoir Production, Case Study in Iraq,” by Xueqing Tang and Zhongliang Cheng, SPE, PetroChina, and Ruifeng Wang, SPE, CNPC, et al. The paper has not been peer reviewed. Halfaya oilfield in Iraq contains multiple vertically stacked reservoirs. The main oil reservoirs are under primary development at the time of writing. The remaining deepest high-gas/oil-ratio (GOR), high-pressure/high-temperature (HP/HT) carbonate reservoir, with an original pressure gradient of 0.867 psi/ft, has been drilled and tested but not yet developed. A production strategy has been proposed in which high-GOR crude can be injected into the upper oil reservoirs with partial pressure depletion as an energy-conservation measure in view of its high wellhead pressure and good productivity during drillstem tests (DST), thereby achieving production enhancement and synergy among reservoirs. Introduction The Halfaya field is a supergiant hydrocarbon accumulation in southeastern Iraq. Structurally, it is a gentle elongated anticline trending northwest/southeast. It is 20–22 miles long and 5.0–5.9 miles wide. It features nine vertically stacked reservoirs, including two sandstone reservoirs with high permeability and seven highly heterogeneous carbonate reservoirs (including Sadi B, Middle Cretaceous Mishrif, and Lower Cretaseous Yamama). The main reservoirs, Mishrif, Nahr Umr, and Upper Kirkuk, contain edge water and bottomwater support. Early field production began in April 2005. So far, 313 wells have been producing and the field has successfully achieved 413,000 BOPD compared with the plateau production target of 400,000 BOPD, with a water cut of 8.7%, producing a GOR of 759 scf/STB.

E&P Notes (March 2022)

E&P Notes (March 2022)

Eigenmode Decomposition of the Diffusion Equation: Applications to Pressure-Rate Deconvolution and Reservoir Pore Volume Estimation

SummaryThis paper proposes the application of the eigenmode decomposition to the problem of pressure-rate deconvolution. The method enabled us to write the solution of the pressure-rate deconvolution as an infinite series of eigenmodes (eigenfunctions). Each eigenmode is associated with a hydraulic diffusion time scale (eigenvalue) that depends on the intrinsic reservoir properties. The set of eigenmodes forms a basis of the solution space and the analytical solution shows some desirable properties: It is smooth, physically constrained for a closed system, and some parameters have a physical interpretation. As a result, in both single and multiwell problems, the late-time unit slope appears naturally and the curvature penalty does not have to be imposed, thus addressing current knowledge gaps. As an additional contribution, we also propose a mathematically well-defined expression in terms of eigenfunctions to the concept of investigated volume during a well test and a procedure for untangling the single-well deconvolved response from interference effects of neighboring wells under certain conditions. Applications to the analysis of drillstem tests (DST) and reservoir characterization are presented.

Seismic Work Flow Characterizes Deep, Thin Formation Layers Offshore South China Sea

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 30164, “Deep and Thin Overpressure Reservoir Characterization of Paleogene Wenchang Formation in the Enping 17 Sag of the South China Sea,” by Jun Liu and Yingwei Li, CNOOC, and Donghai Liang, Schlumberger, et al. The paper has not been peer reviewed. Copyright 2021 Offshore Technology Conference. Reproduced by permission. The complete paper describes an integrated work flow for 3D seismic reservoir characterization of offshore deep and thin layers in the Eocene Wenchang formation (WCF) without sufficient well data. The work flow includes seismic data reprocessing, well-log-based rock physics analysis, seismic structure interpretation, 3D simultaneous amplitude variation with offset (AVO) inversion, 3D lithology prediction, and geological integrated analysis. Formation Development and Objectives The Pearl River Mouth basin (PRMB) on the northern continental margin of the South China Sea has undergone multistage extensional rifts. The Enping Sag lies in the Zhu1 depression, north of the PRMB, and consists of three subsags. Enping 17 is the largest and deepest sag, with an area of 550 km2, and the thickness of Eocene sediments is greater than 3000 m. The deep middle Eocene WCF, with gray lacustrine mudstones, is hydrocarbon-rich and is the major source rock in the area. A wildcat well had penetrated the WCF at an area with a vertical thickness of 380 m. During drilling, the mud weight was increased to 1.46 g/cm3 from 4570 m total vertical depth (TVD) downward because of increasing pore pressure and higher background gas abnormalities in the WCF. A high pore-pressure gradient of 14.5 KPa/m was measured by drillstem test (DST) at a depth of 4641.5 m TVD. Under the protection of the high pore pressure, the high-quality reservoir layer from 4642 to 4651 m TVD was encountered with 12% average porosity, 3.6-md permeability, and 47.1% saturation. Although a hydrocarbon sample was not obtained during the downhole test because of technical restrictions of DST in 1985, gas surge and a small amount of gas and condensate oil were observed after the test instruments were pulled to surface. With the subsequent development of field techniques, it was likely that current drilling and DST techniques could achieve productive oil flow in this layer.

Technology Focus: Well Testing (February 2022)

Bias is always a factor in decision making. To put it a catchier way, “if you have a brain, you are biased.” This was the opening to a recent soft-skills training course I took on the science of better decision making. I left pondering the implications of bias on pressure transient analysis. Well tests are conducted throughout the resource life cycle to establish well and reservoir properties and to optimize depletion planning. But this requires well-test interpretation, which, in turn, requires choosing among nonunique solutions. One key to reducing nonuniqueness is to integrate pressure data with information from other disciplines, including - Routine core analysis, core description, and well logs - Formation-tester mobilities and interval pressure transient tests - Production logging and distributed temperature surveys - Fieldwide production and injection history - Seismic data and geologic understanding This is where technology comes in. New tools have made the unmeasureable measurable and have provided data in larger quantities with improved precision and for longer periods of time. While it may be an engineer’s dream, more and better data do not necessarily lead to better decisions. As with any sound scientific or engineering study, one must think about bias. Is the data being unconsciously cherry-picked to mold the desired outcome? After all, the subsurface is complex enough that multiple assumptions and hypotheses remain plausible; not all information may fit the storyline, and some might be dismissed or underweighted before the full range of possibilities is considered. A critical component of interpretation includes acknowledging one’s own bias and carefully listening to and seriously considering alternative and opposing views. Cold-eyes reviews and devil’s advocates are part of a centuries-old toolkit proven to root out bias, ambiguity, and unnecessary complexity, leading to better-defined problems and, ultimately, better decision making. Interpreting data from new and well-established technologies under the framework of the Socratic method paves the way to a clearer view of the subsurface. This month’s papers demonstrate the continued relevance and diversity of our discipline. The ambitious permeability log, referred to as “elusive” in my column 2 years ago, now boasts a tangible pilot in a Middle Eastern carbonate field. Well tests and cleanup operations do not always require flaring. Alternative fluid-disposal solutions, tailored to project specifics, show potential to meet the timely topic of emissions. Machine learning offers a key to deciphering well connectivity in field data, overcoming noise and other suboptimal conditions. Recommended additional reading at OnePetro: www.onepetro.org. IPTC 21780 - Design and Implementation of a Water-Based Micronized Weighting Agent Fluid System for Deepwater Drillstem Testing Operation in Environmentally Restricted Location by Marcelo Dourado Motta, MI-SWACO, a Schlumberger Company, et al. SPE 205145 - Systematic Application of Pressure and Temperature Transient Analysis in an Oil Field: A Case Study by Khafiz Muradov, Heriot-Watt University, et al.

An Integrated Approach of Numerical Well Test for Well Intersecting Fractures Based on FMI Image

Abstract Fluid flow is strongly affected by fractures in unconventional reservoirs. It is essential to deeply understand the flow characteristics with fractures for improving the production and efficiency of unconventional reservoir exploitation. The purpose of this work is to develop an accurate numerical model to evaluate the transient-pressure response for well intersecting fractures. The meshes generated from Fullbore Formation Micro-Imager (FMI) images ensure an efficient numerical description of the geometries for fractures and interlayers. The numerical simulation is implemented by an inhouse finite element method-based code and benchmarked with drill stem test (DST) data. The results show that three flow regimes appear in the reservoir with fractures within the test period: wellbore afterflow, pseudolinear flow, and radial flow. In contrast, only the wellbore afterflow and radial flow appear for the wells without fractures. The results also reveal that fractures dominate the flow near the wellbore. Verification and application of the model show the practicability of the integrated approach for investigating the transient-pressure behaviors in the unconventional reservoir.

Deep transient testing methodology: An integrated approach to redefine the real-time reservoir complexities and well deliverability

Pressure transient analysis (PTA) forms a critical part of the reservoir characterization and quantitative evaluation of reservoir properties. In most of the cases, the pressure transient data are acquired by conventional drill stem tests (DST) to estimate fundamental reservoir properties like permeability, skin, and boundary, used for various well deliverability studies. However, with the emergence of cost optimization scenarios due to reduced crude oil prices in the market, and strict regulatory standards issued by the concerned governments, many exploration wells fail to pass the feasibility standards for a conventional full-scale drill stem test. At the same time, conventional formation testers couldn't help because of the limitation of its extremely low radius of investigation. The recent development of an improved wireline formation tester (WFT) version known as Deep Transient Tester (DTT) enables the industry to capture the far-field reservoir properties with a deeper investigation, complex reservoir heterogeneities, and possible boundary information. However, the acquired data needs advanced solution techniques for accurate interpretation of the information, which lacks at present. In the present study, we have showcased the development of a novel workflow that can interpret the deep transient testing data with better accuracy. The workflow is called Integrated Deep Transient Testing (IDTT). The IDTT workflow is the first of its kind, as per our knowledge, that utilizes both the analytical and numerical methods for the pressure transient analysis with advancements in each of them. The workflow has been validated by comparing results from three modes of testing DST, DTT, and WFT in a common well. Reservoir engineers can refer to the IDTT workflow to interpret the DTT pressure data to characterize reservoir properties, boundary information, and deliverability studies in simple to complex geological settings using the presently developed method.

Developing a new approach for the anticipation of subsurface pressure in three oil wells from various fields in Iraq

Subsurface pressure quantification is the main goal for all drilling engineers due to its vital importance to minimizing drilling costs and preventing various excavating dilemmas such as stuck pipe, pipe collapsing, lost circulation, and well kick. Formation pressure is measured directly in producing hydrocarbon zones using special equipment; however, it is difficult to obtain pore pressure measurements in other intervals; therefore, many approaches were suggested and developed to anticipate the geopressure due to its importance on the drilling operation. Traditionally, Eaton's method is the most widely used for geopressure anticipation from well logs. In the current study, a new proposed formula for geopressure determination was derived from the modified Eaton's equation which is based on the inception of the mechanical specific energy. The study was applied on three oil-producing wells from different fields in Iraq (Missan C, West Qurna 15, and Zubair 171). The estimated subsurface pressure from the new suggested approach was validated by comparison with the actual in situ subsurface pressure obtained from Drill Stem Test (DST) and Repeated Formation Test (RFT). Statistical analysis is used for the validation by applying Mean squared error (MSE) and Mean Absolute percentage Error (MAE). Encouraging results were obtained from the present research for all wells being studied. The main finding of the current work is involving a new parameter (mechanical specific energy) for subsurface pressure determination, where it was not included in the previous techniques of geopressure equations. It was found that the value of exponent (m) in the new proposed equation has a significant influence on the predicted geopressure, where (m) varies from 0.1626 to 0.6896 depending on the type of the excavated rock plus the materials that the drill bit is manufactured of, where the interaction between these components is vital. The present work could be a useful method when planning to excavate a new well adjacent to the area of the investigated wells, where special well logs are unavailable for pore pressure measurement and suitable usage of mud weight is highly needed for the overall drilling process.

Characterization of the Carbonate Formation Fracture System Based on Well Logging Data and Results of Laboratory Measurements

This article presents a novel methodology for data integration including laboratory data, the results of standard well logging measurements and interpretation and the interpretation of XRMI imager data for determination of the porosity and permeability of the fracture system in carbonate rock. An example of the results of the micro computed tomography applied for carbonate rock is included. Data were obtained on the area of the Polish Lowland Zechstein Main Dolomite formation. The input set of data included the results of mercury injection porosimetry (MICP), thin section and polished section analysis, well logging measurements and comprehensive interpretation and micro computed tomography. The methodology of the macrofractures’ analysis based on borehole wall imagery as well as estimation of their aperture was described in detail. The petrophysical characteristics of the fracture systems were analyzed as an element of standard interpretation of well logging data along a carbonate formation. The results of permeability determination, with micro-, mezzo- and macrofractures’ presence in the rock taken into consideration, were compared with outcomes of the drill stem tests (DSTs).

Research on Productivity Prediction Method of Sandstone Reservoir Based on Logging Permeability Synthesis Technology

Using conventional logging data to accurately calculate drill stem test (DST) permeability can greatly improve the productivity prediction accuracy of offshore heterogeneous sandstone reservoir. Therefore, considering the influence of macro sedimentary diagenesis and micro pore structure on reservoir permeability in Huizhou sag, the logging interpretation models of absolute permeability of different reservoir types are established. Analysis results show that the contribution of reservoirs with different permeability levels in perforated intervals to productivity is obviously different. The synthetic logging permeability is obtained by weighted summation of reservoir permeability at different levels, and the weight coefficient is constrained to highlight the contribution of advantageous reservoirs to productivity. Finally, the regression fitting equation of DST test permeability is established, the optimal solution of DST test permeability equations is obtained by continuous iteration of differential evolution algorithm. This technology is used to predict the productivity of 72 oil layers in Huizhou Depression. For 48 oil layers with productivity greater than 100 m3/d, the proportion of prediction relative error less than 30% is 90%, and for 24 oil layers with productivity between 10-100 m3/d, the proportion of relative error less than 50% is 79%. The productivity prediction method based on new permeability synthesis technology can provide effective guidance for offshore field testing and greatly reduce the cost of exploration.

A new technique for forecasting pore pressure in two oil wells in North Rumaila field based on specific energy concept

Forecasting the pore or formation pressure is crucially significant in every well drilling operation to determine whether the pore pressure gradient is abnormal or subnormal. Abnormal pore pressure gradient means that the pore pressure gradient exceeds the gradient of the normal pressure, while when the opposite happens it means that the pore pressure is subnormal. Both cases required high care with special control of the mud weight to overcome the vital situation. Accurate pore pressure determination is rigorous in drilling engineering to plan for drilling hydrocarbon wells with appropriate mud program with less effort and cost. Precise forecasting of formation pore pressure prevents occurring various drilling hazards such as lost circulation, stuck pipe and well kick as a result of abnormal pore pressure. In the present work, a new technique was proposed to predict the pore or formation pressure from the specific energy. A new formula of specific energy was used involving the rock properties and the drilling parameters. The new specific energy formula is functioned later in Eaton’s equation to obtain a new suggested formula of pore pressure. There is a lack of researches in the literature that determine the real-time pore pressure without depending on well logs. Abnormal and subnormal pressure zones can be determined accordingly based on the fact that abnormal pressure intervals possess low effective stress and require less energy to drill than the intervals that have normal pressure at the same depth. The new proposed formula of pore pressure was tested in two oil wells in North Rumaila field (N14 and N15) in Basrah province south of Iraq. The obtained pore pressure from the new technique based on the suggested specific energy formula that involves the physical properties of the rock being excavated and the drill bit is compared with the actual (measured) pore pressure derived from other wells in North Rumaila field using measurements while drilling logs, drill stem test and real formation test. There was a good rapprochement between the predicted and the measured pore pressure. The present approach depends mainly on the value of the slope (m) which is determined and varied from one place to another. The new method could provide an alternative method for estimating the pore pressure especially for wells being planned to be drilled where the actual pore pressure is unknown and there is shortage in well logs and formation tests, where most of the previous articles in the literature depend mainly on well logs of adjacent wells in predicting the pore pressure of a specific well. The findings of this study can help for better understanding the prediction of formation or pore pressure that helps to choose the appropriate mud weight to control the well without collapsing and preventing well kick that might occur.

Well logging data interpretation for appraising the performance of Alam El-Bueib reservoir in Safir Oil Field, Shushan Basin, Egypt

This paper presents different well log data interpretation techniques for evaluating the reservoir quality for the sandstone reservoir of the Alam El-Bueib-3A Member in Safir-03 well, Shushan Basin, Egypt. The evaluation of the available well log data for the Alam El-Bueib-3A Member in this well indicated high quality as oil-producing reservoir between depths 8108–8133 ft (25 ft thick). The calculated reservoir parameters possess shale volume less than or equal to 9% indicating the clean nature of this sandstone interval, water saturation values range from 10 to 23%, and effective porosity varies between 19 and 23%. Bulk volume of water is less than 0.04, non-producing water (SWirr) saturation varies between 10 and 12%, and permeability ranges from 393 to 1339 MD reflecting excellent reservoir quality. The calculated BVW values are less than the minimum (BVWmin = 0.05) reflecting clean (no water) oil production, which was confirmed through the drill stem test (DST). The relative permeabilities to both water and oil are located between 0.01–0 and 1.0–0.5, respectively. The water cut is fairly low where it ranges between 0 and 20%. Additionally, the water saturation values are less than the critical water saturation (Scw = 29.5%) which reflects that the whole net pay will flow hydrocarbon, whereas the water phase will remain immobile. This was confirmed with reservoir engineering through the DST.

E&P Notes (May 2021)

E&P Notes (May 2021)

New insights on source rock maturation in the southern Gulf of Gabes (Tunisia) via 1-D modeling: effect of combined corrected borehole temperature and thermal conductivity on heat flow distribution

Effective quantitative modeling of petroleum generation processes requires a reasonable knowledge of various factors controlling the transformation of organic matter into oil or gas. Nevertheless, it is widely accepted that thermal conductivity and temperature have the dominant roles in controlling generation. In Tunisia, previous source rocks burial and maturity modeling were mostly carried out using corrected borehole temperature after applying formula which were set to fit domains other than Tunisian basins. The main purpose of this work is to propose a suitable method of temperature correction to fit the studied area but more importantly to emphasize the impact of thermal conductivity on heat flow distribution. For that, a total of 222 temperature values including 170 bottom hole temperatures (BHT) and 52 drill stem tests (DST) were collected from 30 onshore and offshore boreholes. The proposed equation generates corrected temperature close to true formation temperatures. As thermal conductivity depends on the relationships between a sedimentary interval component, two equations were used to determine the conductivity of each unit which are the harmonic and the geometric means. To assess the importance of applied corrections, three scenarios were tested for an Albian source rock using the 1-D Basin-Mod software. The combination of corrected BHTs and thermal conductivity provide higher source rock maturation than when uncorrected data are used. Amounts of generated hydrocarbons are estimated to become two times higher. This would guide for complementary reserves estimations to be applied in the region for better calculation accuracy.