An omission error occurs when independent variables are missing from a regression model. When individual observations are not available, the modifiable areal unit problem (MAUP) appears with spatially aggregated data sets. Both omission error and the MAUP can occur simultaneously in regression analyses. In particular, the MAUP causes the bias due to an omission error to be less predictable for linear regression models, and it distorts bias differently with different spatial configurations. This article analyses the impacts of the MAUP on omission error and shows that the expectation of coefficient estimates at the aggregate level can be decomposed into three parts: the true coefficient, individual‐level bias, and aggregate‐level bias. The findings fill the gap between empirical studies in geography and theoretical results in econometrics, and show that the traditional approaches to the MAUP, such as reporting analyses from multiple spatial configurations, are unhelpful in identifying the correct coefficients.
The Songliao Basin is the largest oilfield in China and across southeast Asia. The Upper Cretaceous Qingshankou and Nenjiang Formations in the basin comprise the source rocks for conventional oil and gas, as well as the primary exploration target for shale oil. Although the lacustrine organic-rich shale (LORS) in the first member of Nenjiang Formation (K 2 n 1) from the southern Central Depression is characterized by high organic matter (OM) abundance and the dominance of oil-prone kerogen, a study on the algal-microbial community, paleoenvironment, and shale oil potential of them is still lacking. Here, we address these issues based on the integration of bulk geochemical, organic petrographic, biomarker, scanning electron microscopic, and nitrogen gas adsorption analyses. The algal-microbial community was mainly composed of red algae, green algae, and dinoflagellates, together with bacteria and a minor proportion of land plants in the paleolake, which might be favorable for OM productivity. Saline to brackish and anoxic to dysoxic conditions were present in the paleolake, which were conducive to OM preservation. Both the favorable OM productivity and preservation conditions resulted in deposition of the K 2 n 1 LORS, which was characterized by high total organic carbon (TOC) contents and the dominance of oil-prone kerogen (type I). However, limited hydrocarbon generation potential of shale oil was present in the K 2 n 1 LORS, because of the relatively low maturity (early oil window maturity). Nano- to micrometer pores, including interparticle pores, intracrystalline pores, dissolution pores, and OM pores, formed two types of pore structures and pore size distributions in the K 2 n 1 LORS. In comparison with LORS from the first member of Qingshankou Formation (K 2 qn 1) in the study area, the K 2 n 1 LORS displays higher TOC and HI values, lower OSI and T max values, and a higher Brunauer–Emmett–Teller surface area and Barrett–Joyner–Halenda pore volume. The favorable area of shale oil in the K 2 n 1 LORS is proposed based on the integration of OM abundance, type, and maturity. In addition, the K 2 n 1 LORS buried with a depth of <1000 m may have great oil shale potential, which is suitable for in situ conversion processing. However, further research on the planar distributions of oil yield, shale thickness, underground water, laminar fractures, and OM pores of the K 2 n 1 LORS are needed. This work is not only beneficial for paleoecological reconstruction in the Songliao Basin during the K 2 n 1, but also provide guidance for regional unconventional hydrocarbon exploration in the future.
In some cases, the oil shale deposited in shallow lakes may be genetically associated with the coal-bearing successions. Although paleovegetation is an important controlling factor for the formation of oil shale- and coal-bearing successions, few studies have focused on their joint characterization. In this study, a total of twenty-one oil shale and coal samples were collected from the upper member of the Lower Cretaceous Muling Formation (K1ml2) in the Laoheishan Basin, and investigated for their bulk geochemical, maceral, palynological, and terpenoid biomarker characteristics, in order to reconstruct the paleovegetation and reveal its influence on the formation of oil shale and coal. The K1ml2 is subdivided into lower, middle, and upper units. The studied oil shale samples from the lower and upper units display a high ash yield (Ad), low total organic carbon (TOC) and sulfur (S) contents, and limited hydrocarbon generation potential. The studied coal samples from the middle unit are characterized by low Ad, and high TOC and low S values, and show significant hydrocarbon generation potential. The paleovegetation during the formation of the lower unit was dominated by mire vegetation, such as shrubs (e.g., Lygodiaceae, Schizaeaceae), tree ferns (e.g., Dicksoniaceae/Cyatheaceae), and coniferous trees (e.g., Podocarpaceae). In the middle unit interval, the paleovegetation was represented by highland vegetation (Pinaceae and Araucariaceae) and peat-forming coniferous plants (e.g., Podocarpaceae, Cupressaceae/Taxodiaceae). Various vegetation, such as herbs (e.g., Osmundaceae), shrubs (e.g., Schizaeaceae), and coniferous trees (e.g., Podocarpaceae) was prosperous during the upper unit interval. Coniferous trees could provide abundant hydrogen-rich materials (e.g., resins) to the mire/lake, which may elevate the hydrogen content in peat/lake sediments, and finally result in higher hydrocarbon generation potential in the coal than in the oil shale. Therefore, the influence of paleovegetation on the formation of oil shale and coal should be fully considered when studying oil shale- and coal-bearing successions. The results also provide guidance for further exploration studies on oil shale and coal in northeast China.
As a new field in the service industry, logistics is growing rapidly and is regarded as a fundamental industry in a national economy. Its development is an important symbol of a country’s modernization and national strength. It also works as an accelerator in economic development. At the initial stage of transforming traditional logistics service to a modern logistics service in China, logistics enterprises have encountered many difficulties and problems including an imbalanced supply and demand, distempered industrial structure, faultiness of serving process and backwardness of logistics technology since 2005.Compared with developed countries, there is a great gap between Chinese logistics enterprises and advanced countries’ in the aspects of service concepts, model, and content and techniques. Therefore, based on the service innovation driving model theory, the authors analyze the integrated innovation model of logistics enterprises, logistics technology and network model, and the value-added service model. The authors select Shenzhen China Overseas Logistics Co. LTD (COL) as the empirical object to analyze its operation of technology and non-technology innovation and summarize its inner and outer driving force on promoting service innovation.
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